As we sharpen our focus for 2020, we reflect back on the product investments we’ve made in 2019 to help our customers drive deeper, more meaningful learning within their organization. While helping employees do whatever comes next is foundational to shaping our product roadmap, customer feedback is a powerful driver of the enhancements we make and the features we build. We’re excited to share how we’ve incorporated these valuable inputs in our product development to help global organizations successfully upskill their workforce.
Driving more purposeful learning
We have resounding feedback from customers that the most effective learning often happens when it’s recommended by a colleague, team lead, or an SME within their organization. Research from a recent study by Degreed and Harvard Business Corporate Learning found that employees are constantly seeking information in the flow of work.
To bring together a powerful learning experience that harnesses the collective knowledge of an organization and leverage resources beyond Udemy for Business courses, we created Learning Paths. Anyone at a company can create a learning path to share and socialize learning by combining resources in one place: fresh, high-quality Udemy for Business courses and lectures, internal links like Wiki articles or shared docs, external links such as podcasts or articles, and custom courses for easy access.
This is an effective way to help customers streamline onboarding, build custom career growth paths, or upskill for a new project that requires a new set of skills. We are continually optimizing our Learning Paths feature to make it more robust so that companies can achieve learning outcomes even faster and more efficiently.
Reaching learning goals faster
Managers, L&D professionals, or those that drive learning at an organization wanted the ability to easily assign relevant content to learners. By listening to this feedback, we made enhancements to our course assignment. With features like due dates to drive completion and engagement, more tools to track progress, and notifications to ensure learners stay on track, our goal was to provide learning professionals with simple but robust functionality to drive learning. Both courses and learning paths can be assigned for a more guided learning experience.
More forms of content, more engagement
Our Udemy learning data shows that shorter forms of content tend to lead to increased learning engagement. Knowing that employees have limited time to learn, we wanted to maximize their time and increase the impact of learning. That’s why we introduced Smart Tips — courses that are 3–8 minutes long to help learners attain their goals, reinforce learning, and apply new skills quickly. Each Smart Tip can be immediately applied in the areas of Communication, Excel, and Productivity.
We’ve also heard from customers that it is vital for non-technical teams to understand technical content as well. Whether it’s the CEO becoming conversant in key technologies to communicate with their Engineering or Product team on key initiatives, or the Sales teams understanding the enhancements technology brings to their product, it’s essential to gain an understanding of what various technologies are and the key concepts of how they’re applied in business.
That’s why we’ve created Executive Briefing courses. These are short courses that break down complex technical topics for anyone to understand. In 2019, we introduced Executive Briefing courses on Machine Learning, Artificial Intelligence, and Big Data, and plan to introduce additional topics in 2020.
Extending the value of Udemy content
We want our customers focused on achieving learning results and not on the administrative burden of managing learning. Therefore, we were committed to helping organizations that leverage Learning Management Systems to easily gain access to our top-rated Udemy for Business content for their learners. This year, we extended our learning partnerships with top leaders in the industry to make it even easier for learners to engage with Udemy content through their current LMS/LXPs.
Whether it’s content or product enhancements, we are committed to bringing the customer voice into how we build the product. We’ve made some fundamental, powerful changes to our product, and we’re thrilled for what’s in store for 2020. A big thank you to our global customers for providing insightful feedback that helps improve our product.
As 2020 begins, it’s time to consider which technical skills you and your team should master for the year ahead. Whether you have goals of advancing your career in programming, taking your company’s infrastructure to the cloud, or discovering deep customer insights using data and artificial intelligence, we’ve outlined in this article the technical skills that software engineering, data science, and IT professionals needfor success in the decade ahead. These skills are foundational for both your career and building successful teams in programming, web development, data science and AI, cloud computing, and IT. Based on the learning habits of 50+ million Udemy users, here are the 10 most popular technical skills we see trending on Udemy and the skills you and your team should prioritize in the coming year. For more hot skills, download 2020 Workplace Learning Trends Report: The Skills of the Future.
10 most popular technical skills of 2020
How does a programming language become the fastest-growing and most popular language of 2020? In addition to being the language of choice for data science and artificial intelligence applications, Python is #1 on our list thanks to its simplicity, which makes it a great language for beginners to learn and for companies to use to scale their products. Instagram was able to grow its app to serve one billion global users through Python. You don’t need to have a decade of computer programming experience to get started in Python. The language uses less code than others, which helps it read more like English and has fueled its adoption with programmers of all levels.
One of Python’s greatest benefits is the number of open-source libraries built on the language. Python libraries like TensorFlow and PyTorch for machine learning or PyGame for game development are collections of modules that a developer can use for frequent commands rather than taking the time to write and rewrite common code.
The community Facebook built for React users propelled its popularity. As a result, thanks to its ubiquity on development teams, React is often cited as one of the most important web development skills for programmers and teams to learn.
Mobile app downloads are expected to reach 260 million by 2022. Consumers split their screen time across multiple devices every day, with arguably more focus on the mobile smartphone and tablet screens that can travel anywhere versus desktop. Providing the same rich, interactive desktop experience to a mobile audience is more important than ever, which is where React Native steps in. As a result, React Native is the #3 most popular technical skill trending on Udemy for 2020.
As a separate library from React.js, React Native is a collection of special React components that are compiled into native widgets for iOS and Android mobile platforms.
React Native also provides access to APIs native to the mobile platform you’re developing for such as the use of a device’s camera. These capabilities are crucial for development teams to ship high-quality native apps to the Apple App Store or Google Play Store without having to teach their teams platform-specific skills like Swift for iOS or Java for Android.
As a subset of artificial intelligence, machine learning uses algorithms to learn from large datasets and is the #5 most popular technical skill trending on Udemy in 2020. This differs from other data analysis approaches that require explicitly programmed instructions to derive insights. Machine learning techniques are best used for understanding highly complex and non-linear data.
Data scientists are most likely to use machine learning for classification and prediction of unknown data. An algorithm is programmed to learn from a dataset filled with millions of data points and then tasked with finding insights or trends based on patterns within that data. Machine learning techniques like classification have become common as digital services ingest and analyze data based on customers’ every click of a button. For example, the recommendations your favorite streaming platform makes after you’ve finished a movie? A machine learning algorithm was hard at work analyzing the platform’s movie options and referencing those against your previous viewing habits.
Docker is a platform that makes it easy to install and run new software on a computer. Specifically, the Docker platform operates around creating and running containers. What’s a container? As Udemy instructor Stephen Grider explains in his course, Docker and Kubernetes: The Complete Guide, a container is a program with its own isolated set of hardware resources including memory and networking technology.
Docker allows developers to configure containers to the specific dependencies, operating systems, and libraries required for an application. These tailored containers can then be used across computing devices. From your desktop to a colleague’s laptop to a Linux cloud server, one container ensures all these devices run on the same configuration. This consistency is how Docker has become essential to a DevOps software development process. Teams can onboard quickly to a standardized software environment, collaborate on code with colleagues around the world, and even save money by running multiple containers on a single virtual machine rather than the costly alternative of one piece of software per machine. Due to these benefits, Docker is the #6 most popular skill trending on Udemy for 2020.
Django is another web framework that is #7 on our list of popular technical skills trending on Udemy for 2020. This high-level Python framework is great for beginners because it’s so easy to learn. Though it was first introduced 12 years ago, the framework saw a refresh in 2019 with Django 2.2. The Django framework offers features that create the infrastructure for database-driven websites, according to Udemy instructor Nick Walter. This includes the creation of contact forms, user authentication, file uploads, and more.
These features can be developed quickly with the use of command-line tools for creating projects and apps and migrating data. As Udemy instructor Brad Traversy notes, Django allows you to build something in a month that would take at least six months to build from scratch. In other words, Django helps developers build complex websites with little code. Another reason to opt for Django in a future project? It helps websites scale with business needs and offers built-in security features.
Among the most in-demand IT certifications, the Computing Technology Industry Association (CompTIA) is the #8 most popular technical skill trending on Udemy. Over 9,000 IT professionals, educators, and students in the US are CompTIA members, a non-profit trade association known for its IT training. Since the organization’s training is vendor-neutral, professionals learn IT skills that aren’t specific to one provider like Microsoft or Apple. CompTIA offers 12 certifications across IT fundamentals, networking, cybersecurity, cloud computing, and more.
Where to get started with CompTIA? The CompTIA A+ certification provides a well-rounded education in the subject matter an IT manager wants their teams to have expertise in, including knowledge on networking, cloud computing, and virtualization.
In the age of digital transformation, IT budgets are directed to tools that speed up technical efficiencies, which include cloud computing services like Amazon’s AWS. The cloud computing industry is expected to see three times the growth of other IT services through 2022, according to a Gartner forecast. With AWS holding a 47.8% market share over competitors like Microsoft’s Azure or Google Cloud, AWS proficiency is an essential skill for IT specialists and software engineers.
Though deep learning research has been underway since the 1960s, it’s grown in popularity in the last decade as computer hardware has become powerful and affordable enough to power the processing needs of this AI specialization. The goal of deep learning is to mimic the intricate learning style of the human brain. By using tools like TensorFlow and Python, deep learning scientists create artificial brain structures, known as neural networks, to simulate the biological neurons of a human brain.
These neural networks can perform more complex tasks than machine learning algorithms. Neural networks can identify objects in images, such as classifying with remarkable accuracy whether a photo depicts a cat or a dog. Classification networks like these can be used to improve self-driving cars’ ability to identify objects on the road and distinguish another car versus a human. As AI is poised to reshape businesses in 2020 and beyond, it’s not surprising deep learning is the #10 most popular technical skill trending on Udemy.
With the new year beginning, you and your employees may be thinking about promotions, leadership, and taking the next career step. While these ambitions are admirable, it’s no secret that taking on a broader leadership role is challenging. We’ve known for more than 20 years that more than 50% of leaders who take on broader assignments fail within the first 18 months. Why is it so hard for executive-level leaders to succeed? What are some of the most common mistakes they make and how can your organization and executives avoid them?
To answer these questions, I conducted a ten-year longitudinal study on executive transitions to isolate leadership strengths and recurring patterns that distinguished exceptional executives. One of my major discoveries was the vast majority of leaders say they felt unprepared for the challenges of leadership they discovered when they took bigger jobs. And more than half of them didn’t have any ongoing coaching to help them once in the role. That’s why I set out to help leaders understand the skills they need to succeed in those bigger roles. I’ve written about this topic at length in my book Rising to Power and cover this content in depth in my Udemy course Exceptional Leadership: Leading at a Higher Level.
In this post, I’ll provide four tips for success when you or your employees arrive in a new leadership role.
Proactively preparing for arrival at a higher level all begins with actually having a plan for that transition. And while these activities are best done at the outset of the leadership transition, they can be useful at any point in the leadership journey.
1. Build a robust learning plan
Every leader enters a new role with a set of assumptions about what lies ahead. The problem is, those assumptions will naturally miss important perspectives and information. New leaders need a way to gather objective information about the current state of the group they will be leading, its current level of performance, and how people are feeling about the future of the group. Whether new leaders conduct a survey, have an outsider or HR business partner conduct interviews, or have a third-party conduct focus groups, new leaders must build a robust learning plan that uncovers the things they inevitably don’t know.
A rich data set will help you and your team confirm that some of your assumptions were correct while completely upending other assumptions, replacing them with more reliable perspectives and information. The data also will allow you and your team to align around a common story. Leadership transitions naturally fragment an organization, as people hunker down waiting to see what the new leader will be like. Everybody will have their own version of the story. A solid assessment allows new leaders to bring everybody onto the same page, drawing a common set of conclusions about the current story, and helping shape the shared story they want to create together going forward.
2. Create a synthesized set of priorities
Once new leaders have gathered sensitive data, including disconfirming data that offsets assumptions, the next step is to construct an additional set of priorities to focus on and align their team around. Newly promoted leaders often forget that their arrival is a disruptive jolt for the organization. It sets people off balance as they speculate about what changes the leader will make, how those changes will depart from their predecessor’s agenda, and how those changes will affect them personally. Anxious conjecture drains the organization of focus and energy that’s necessary for executing the new leader’s plan.
Leaders who understand the context before they give the organization its marching orders know that less is often more and setting up small wins parlays into needed momentum and bigger ones later. Leaders who fail to understand this reveal grand plans that paralyze the organization with too many priorities and bury everyone under the weight of massive work in addition to their day jobs. Worse, these leaders tend to ignore the organization’s indifference to the plan’s unrealistic scope and lack of credibility until it’s too late. New leaders must distill their plan into two or three critical priorities everyone agrees are important and everyone feels committed to tackling.
3. Size up talent and build your team
One of the hardest parts about being promoted or taking on a broader leadership role is inheriting a predecessor’s team. Sure, it would be great if everyone on the team had to “re-up” for their job, but unfortunately that’s not how it works. A lot of factors influence whether or not the existing team is the right team for the new leader and the direction in which they want to take the team and organization. This can include their track record of performance, how receptive they are to new leadership, how overtly they try to curry favor with new leaders, how subtle they are about throwing their teammates under the bus when sharing their views on “what has to change,” how capable they are of delivering against the results you need, and how genuinely they resonate with the vision new leaders are forming.
New leaders must form a systematic way to assess the talent they have against the agenda they are forming to determine who can stay, who can grow, and who must go. Many newly appointed leaders are reluctant to make hard calls, especially early in their tenure. They fear alienating their team and sending political shockwaves through the organization by removing people who, though once thought of highly, will clearly be immovable obstacles to change.
Whether through a lack of competence, commitment, or both, not everyone will be able to make the journey, and the sooner new leaders are honest about that, the sooner they will get a team around them that is aligned to their vision and willing to do the required heavy lifting. I am not a fan of the “clean house on day one” approach, by any means. The same principle of “taking time to learn” we discussed earlier especially applies to assessing talent. But once the data is clear, new leaders should act.
4. Put in place a way to solicit and act on personal feedback
A way to calibrate is critical to early success. It helps new leaders ensure that they don’t derail before they even know they’re in trouble. The lagging indicators for whether or not you’re getting traction are insufficient and unreliable for determining if you are “sticking” or not. This is especially important in the first six months, when people are still forming impressions of new leaders and their network is unformed and data sources are limited.
Whether through an online survey tool or third-party interviews, new leaders must have a reliable barometer to know if the messages they are sending, the vision they are casting, leadership they are modeling, the plans to which they are holding people to account, and the changes they’re initiating are all being absorbed the way they want them to be. Feedback loops that help them quickly determine whether they are on course allow them room to maneuver and course correct.
One of the greatest challenges of being newly promoted is how easily your words and actions are misinterpreted. New leaders shouldn’t assume that just because they are new to their role that people won’t be able to or willing to provide helpful feedback.
The key to getting great feedback that calibrates is acting upon it. Too many new leaders graciously invite feedback to establish the look of openness, but damage their credibility by doing nothing with it. Make sure you and your employees are overtly appreciative of the feedback you get and let people know how you intend to apply it.
I hope you recognize how important these four parts of a transition plan are. Get disconfirming data, use it to set a vital few priorities, size up your talent and build your team, and have a way to calibrate your own leadership with feedback. If you and your new leaders do these things early in your assignments, you’ll greatly raise the odds of your success.
Office culture is always evolving, but with the influx of younger workers, the increased ability to work remotely, and the prevalence of personal devices and social media, it feels like recent years have brought some significant shifts. In the 2019 Workplace Boundaries report, Udemy set out to explore the current state of personal-professional boundaries in the workplace, how people are navigating these boundaries (or not), and the effect they have on both employees and companies.
What’s the definition of appropriate office behavior?
While many employees are glad they don’t need to purchase a closet’s worth of suits and adhere to a strict corporate hierarchy, what’s rubbing many the wrong way is the lack of understanding around what constitutes professional behavior at work.
Why is this happening? One contributing factor may be a change in employment trends. For one thing, many entry-level jobs, such as administrative assistants and coordinators, have been eliminated due to automation or organizational decisions. Those were traditionally the places where new workers learned the ropes from a close supervisor. In addition, fewer young employees are entering the workforce with summer job experience (only about a third of teens have summer jobs). As a result, they aren’t as familiar with workplace norms when they secure real office jobs, but no one is explicitly tasked with helping them figure it out.
Our research indicates that the workplace is fraught with questionable behaviors and crossed boundaries, from oversharing personal information and gossiping to far worse offenses, such as condoning or ignoring body-shaming and bullying. Furthermore, we get the sense that many companies are not doing enough to curb this behavior or clearly communicate expectations.
Taken together, this suggests an urgent need for companies to create safe spaces where leaders and individuals can discuss workplace behaviors and communicate their norms and expectations to each other. Otherwise, employees won’t know whether their idea of a respectful, professional workplace aligns with what their coworkers have in mind. For example, our research found that 37% of respondents believe their coworkers are too informal in workplace chat or messaging. Without proper training, they won’t have tools for assessing what’s appropriate or resolving conflicts that arise.
“There are a number of reasons that business leaders are struggling with workplace boundaries,” according to Deborah Grayson Riegel, an executive coach, speaker, and CEO of Talk Support, who has taught management and communication at the Wharton School of Business and Peking University. “It often starts when managers in organizations wrongly assume that their workforce ’just knows’ how to interact with each other, not realizing that those expectations must be explicitly discussed, and often vary company to company, as well as across cultures.”
Other outside research has found that there’s a crisis in management. Gallup reports that just 18% of managers demonstrate a high level of talent for managing teams and that promotions to managerial positions are typically based on factors like tenure and performance in a past role, rather than potential to excel in the next one. This is a real liability, as the skills needed for management are completely different from those for an individual contributor. Millennial workplace consultant Aaron Levy explained in the 2018 Udemy Employee Experience Report that, when people move into management, 30-40% of their time shifts from “doing work” to dealing with people issues.
For example, more managers than non-managers say they let work take precedence over meals and relaxation time, with 59% of managers (vs. 46% of workers) revealing they feel pressured to work through lunch or eat with coworkers (63% of managers vs. 50% of workers).
While longer hours may be expected of those moving into management, without effective preparation, managers may find themselves spending a disproportionate amount of time learning on the fly. Perhaps another side effect of this lack of preparedness, managers say they’ve experienced or witnessed inappropriate or discriminatory behavior at work more than non-managers.
Fifty-three percent of managers (vs. 49% of workers) have witnessed inappropriate behavior related to a coworker’s political or social beliefs, opinions, or attitudes. In addition, 42% of managers (vs. 36% of workers) say they have witnessed body-shaming in the workplace, and 55% of managers (vs. 46% of workers) say they have heard inappropriate discussion of personal relationships and dating. A shocking 66% of all employees have either witnessed or experienced bullying in the workplace.
Workplace boundaries must be clarified
Currently, there’s very little dialogue and clarity around acceptable workplace behavior. This puts a lot of pressure on managers and employees to figure it out in real time. To support employee happiness and productivity, as well as reduce turnover, it’s imperative that companies support different personalities and work styles by opening the lines of communication around how to coexist peacefully and productively. “An important part of our role as people leaders is to start the conversation. For some organizations, those discussions will reveal whether any boundaries are being crossed, and for others, the dialogue will focus more on how to navigate challenges that have already been identified,” said Cara Brennan Allamano, SVP of Human Resources at Udemy.
“We spend time asking our employees about perks and career opportunities, but it’s time to also ask how we can create an environment where our people feel supported to work more effectively,” adds Allamano. “Noting the ‘silent majority’ uncovered by our research, I would urge leaders to move past assumptions and ask the questions that will provide an authentic picture of their workforce.”
A good place to start would be for leadership to help managers, teams, and individuals establish their own boundaries, since every group and person is different, and there’s no clear consensus on what’s “right.”
We’d like to believe that the holidays are a happy time for spending time with our loved ones — and they can be. But they can also be a time where our stress is heightened. Research shows that stress tends to increase over the holidays and women experience stress during this time at much higher rates than men. In our everyday lives, common stressors include work, traffic, bills, and caring for our families, and around the holidays we still have all that, along with a sense that our time and money are even more limited than usual. At work, we may feel the pressure of upcoming performance reviews and end-of-year deadlines while covering for others who are away. And while stressors can be both personal and professional, we can’t clearly separate them. When we’re feeling overwhelmed by things at home or in our personal life, it does seep into our professional life and vice versa.
Yet stress isn’t always bad — the problems arise when stress operates in the background of our lives and controls us. As the late great William James, the American father of psychology said, “our greatest weapon against stress is our ability to choose one thought over another.” In my course The Stress Detox: Reduce Stress and Burnout in the Workplace, I help learners make intentional choices and become “stress detectives.” When we understand where stress comes from and how it affects us, we can control stress and use it to our advantage.
Simply put, stress is an internal alarm system that is keeping a pulse on our safety. It signals to our mind and body to respond when change occurs, or when it perceives a threat. The body responds to these changes physically, mentally, and/or emotionally driving our behaviors. What’s important to note is that stress is a process, which means there’s a spectrum of stress that ranges from good to bad to ugly and everything in between.
In this post, I’ll share an overview of my 3D framework for taking control of stress. It’ll be especially important for you and your employees this holiday season, but can be applied throughout the year.
The 3D framework for taking control of stress
Part 1: Develop awareness of stress
There’s no shortage of information out there about what to do about stress, but I recommend slowing down, stepping back, and first figuring what exactly you are trying to do something about. Using the 3D framework you and your employees will first develop this awareness muscle. This is akin to turning on an internal flashlight to discover where stress is hidden in your lives by observing your own stress symptoms.
Once we are aware of these symptoms, we can investigate further to discover what is at the source of our stress. And knowing this information, you and your employees will be ready to do something about it.
One of the best ways to develop self-awareness is through meditation. A regular practice of sitting quietly with your thoughts helps you better understand yourself and the emotions you’re experiencing in any given moment. If meditation is unfamiliar to you or your employees, check out my guided meditation video here.
Step 2: Discover how stress manifests
Gallup defines the five areas of well-being as financial, social, career, physical, and community. Here’s a quick definition of each one.
Your career well-being is about how you occupy your time or simply liking what you do every day.
Your social well-being is about having strong relationships and love in your life.
Your financial well-being is about effectively managing your economic life.
Your physical well-being is about having good health and enough energy to get things done on a daily basis.
Your community well-being is about the sense of engagement you have with the area where you live.
In each of these areas, we can observe the symptoms of stress — provided that we are actually taking the time to notice, which is why developing awareness is the first step!
Once you and your employees understand how stress appears in various aspects of your lives, it’s time for the last part of the 3D framework: do something about it.
There are many ways to help reduce stress, and I encourage you and your employees to experiment with these different stress detox strategies and find what works best. To alleviate the physical symptoms of stress, try dancing, yoga, eating healthy, and staying hydrated.
Taking a mental break is difficult when there’s so much around competing for your attention. To relieve the mental symptoms, try meditating, alternate nostril breathing, celebrating little wins, and saying “no” and setting boundaries.
Cultivating positive emotions whether individually or in your workplace has been shown to improve productivity, decrease stress, and reduce absenteeism. Oxytocin is largely responsible for this. When we genuinely connect with and care for others, we elevate oxytocin, leaving us feeling good and less stressed. A few oxytocin-boosting activities include hugs, pet therapy, laughter therapy, gratitude, and self-compassion. Be sure to check out my course, The Stress Detox: Reduce Stress and Burnout in the Workplace, for how to apply this 3-D stress management framework in your workplace and personal life.
What can be done at work
There are a number of things company leaders and HR teams can do to promote awareness of stress and reduce its effects in the workplace. Here are a few of my suggestions.
Companies are investing more time and resources into strategically creating culture primarily because research shows that positive culture supports innovation and productivity. One way it does this is through reducing stress. Having a culture where employees feel safe, have a sense of belonging, and are valued as humans first creates a built-in support system to leverage as stress relief. This creates a perception of stress as a positive challenge and allows for more resilience.
Mentoring and professional development
This goes hand in hand with culture. Having resources to support employee growth and development keeps them challenged while equipping them with tools and resources to complete difficult projects.
Managers as agents for change
Managers play a huge role in mitigating workplace stress simply by showing up as leaders who see their staff as humans first. By building in simple habits like starting a meeting with a mindful moment, encouraging employees to block out white space on their calendars, and approaching mistakes with curiosity vs. criticism can do wonders for workplace stress.
Carve out time for well-being
Having a culture of well-being is one where employees have access to and are encouraged to use health and fitness tools, healthy food options, mental health resources, personal coaching, and more. Around the holidays, you’ve probably already planned retreats or parties or other gatherings, but I recommend carving out a small amount of time to focus on well-being during these events. You might bring in an outside coach for a quick workshop or you could have a leader take a moment to acknowledge that it’s a stressful time of year and open up a dialogue that way.
As companies prioritize digital transformation, fluency in cloud computing basics is becoming an important skill for even those in roles not traditionally considered technical.
Cloud computing is an industry poised for continued growth as businesses of all sizes move their technical operations off-premise to flexible cloud offerings. Gartner projects that the cloud computing industry will see 3 times the growth of overall IT services through 2022. In the Udemy for Business 2020 Workplace Learning Trends Report, AWS was named among the top 10 fastest-growing skills for the IT, government, nonprofit, and retail industries. Cloud computing knowledge, in general, was named among the top skills shortages for 2020 by learning and development leaders surveyed for the same report.
As demand for cloud computing grows, so does AWS’s leadership in the industry. In 2015, AWS reported revenue of $1.57 billion. This number ballooned to revenue of $25 billion in 2018. In Gartner’s 2019 Magic Quadrant for Cloud Infrastructure as a Service report, AWS was the leader over competitors including Microsoft, Google, and IBM, with a 47.8% market share. AWS is a cloud computing vendor professionals are likely to encounter at some point in their careers, making the Certified Cloud Practitioner exam a meaningful career investment.
The AWS cloud practitioner credential imparts foundational knowledge of cloud computing to beginners and non-technical professionals who want to know how to “speak cloud.” If you’re in a tech-adjacent role, you will find this certification especially relevant.
Cloud computing delivers IT resources like compute power, storage, databases, virtual machines, and more through a web-based platform. Public cloud platforms like AWS own and maintain the costly hardware, such as servers and data centers, required for these IT services. What makes it a game-changer for companies is the ability to easily scale technical operations on-demand and to pay for only the services used for as long as they’re used. No investment in on-premise hardware is required.
Traditional on-premise IT services have high operational costs and require continued upkeep by many on-site employees. Cloud service providers can offer lower costs thanks to economies of scale. Because multiple customers share the same underlying resources, like a networking system, that trickles down to considerably lower costs as compared to legacy IT offerings.
7 non-technical roles that need AWS skills
Since the AWS Certified Cloud Practitioner exam requires a holistic view of the AWS ecosystem and its business offerings, I recommend this certification for just about anyone working in a company or industry that is using AWS or considering moving to public cloud providers. That’s likely you!
This certification will help non-technical professionals “speak cloud” and ensure they’re communicating effectively with customers and cross-functional colleagues. Completing the exam is also an important first step for anyone wanting to pursue more technical AWS Associate-level certifications. So, exactly who should take the AWS Certified Cloud Practitioner exam? Roles adjacent to technical roles that would benefit from basic AWS Cloud skills include:
Project managers: Since project managers work collaboratively with stakeholders of many functions, both technical and non-technical, proficiency in AWS basics will make those collaborations much smoother.
Sales teams: When selling to a prospect or negotiating a renewal with a customer, sales representatives must talk the talk when it comes to technology. Whether working directly with AWS or in a tertiary technology, speaking confidently about cloud computing may help close the deal.
Marketing teams: Similar to sales teams, those building marketing materials and campaigns related to AWS in any way can’t expect to capture their audience’s attention if they’re not speaking the same cloud language.
Executives: In the age of digital transformation, leadership teams from directors to the C-suite should understand the wide-ranging implications cloud computing technology has on a business — from budgets to competitive advantage to employee productivity.
Legal teams: The global reach of AWS and its regional services is a big benefit for companies, but it brings with it security and compliance issues. Legal teams will find this certification beneficial for ensuring their company adheres to geo-specific compliance and security standards.
Finance teams: Because public cloud services are a variable expense dynamic to a company’s growth, finance professionals will have a better grasp of budget allowances by learning more about the pricing variables implicit in the AWS platform.
Beginner-level IT and tech professionals: With AWS the market leader in cloud computing, it’s likely that professionals new to IT will use Amazon’s platform at some point throughout their careers. Make your resume more attractive to recruiters or set yourself up for a promotion by demonstrating mastery of this in-demand skill.
Key AWS skills non-technical roles should master
I designed the AWS Certified Cloud Practitioner Ultimate Exam Training course with the non-technical professionals listed above in mind. The course equips students to pass the exam with a high-level understanding of AWS. The AWS platform offers over 160 services, so we focus on the following priorities that have the most relevance to the non-technical AWS user:
Global infrastructure: AWS has extensive resources around the world. Its infrastructure is divided into 22 regions, which are then supported by many smaller data center availability zones and edge locations. Amazon created this layered architecture to ensure customers have high availability and reliable performance. For instance, if the server powering a company’s website goes down in Availability Zone A, the nearby Availability Zone B can take over website deployment since it was designed as an independent failure zone.
The logistics of the AWS physical infrastructure are important for organization-wide stakeholders to understand. Any downtime can have significant ramifications across business units, especially when it comes to customer satisfaction.
Security in the cloud: Ensuring the security of customer data is a necessary piece of any company’s digital transformation strategy. This is why it’s imperative for even non-technical staff to understand the best practices of data and infrastructure security in the cloud.
While the exam covers a high-level review of key AWS security services, it’s particularly important for the non-technical employee to learn the AWS Shared Responsibility Model. This outlines the cloud security components Amazon is responsible for (e.g. properly building secure components) versus what the customer is responsible for (e.g. properly configuring networks and data encryption).
Pricing model: The 160+ services of AWS can be finely calibrated to make the most of a company’s budget and technical needs, but that requires a high-level understanding of the AWS pricing structure. Of course, financial roles may be the most interested in how AWS structures its pricing, but it’s also an important topic for project managers, executives, and technical team leads.
Non-technical stakeholders will want to understand how AWS constructs its pricing based on the use of compute, storage, and outbound data transfer services. The costs of these services are then broken down into “instances” based on how often they’re used. Examples of these instances include:
On-demand instances with no contract required and charges accrued based only the seconds used of the service.
Scheduled instances can be purchased on a recurring schedule such as daily, weekly, or monthly for a one-year timeframe.
Spot instances let users save up to 90% in typical compute costs by requesting the use of unused compute instances within the AWS cloud system.
Dedicated instances run a virtual private cloud on hardware dedicated to a single customer. This is an expensive option that most companies will shy away from.
To prepare you to pass the exam, my AWS Certified Cloud Practitioner course includes two full-length practice tests, which are timed to mimic the real exam environment. Taking a technical exam doesn’t have to be intimidating even if you don’t have a technical background. Proficiency in cloud services and how AWS cloud can enhance an organization’s productivity will set companies and individuals apart in the next decade.
Many people are confused by the term “strategic thinking,” mistakenly believing that it means thinking big thoughts or reading about others’ — or having your own — big ideas. To put it simply, strategic thinking is about creating a line of sight from your job to the most important things your organization is working on in terms of how it makes money and differentiates itself from competitors. Employees at any level can — and should — take the initiative to make the connections between their company’s strategy and their own work to make sure they’re prioritizing their work, time, and skills accordingly.
For example, someone who works as a social media manager may think their job is about posting content on social media. And yes, their daily work probably involves sharing articles, photos, etc., but what they’re really doing is helping their company build a strong reputation for being, for example, socially responsible, which is one of the ways they’re differentiated from their competition. This would, of course, influence the kinds of stories and posts this social media manager chose. It’s important to make that connection between what someone does on an individual basis and what their company has said it cares about.
In my course, Being Strategic: Thinking and Acting with Impact, I offer a number of approaches and tools to help employees at all levels develop their strategic thinking skills. Here, I’ll share an overview of a few of the concepts that I cover in greater detail in the course.
It’s a common misconception that strategic thinking is an activity that’s reserved for senior leaders. And it is true that senior leaders tend to spend more of their time thinking about the future. Generally, the more senior a role is, the further into the future they’re focusing. Being strategic doesn’t simply mean thinking long-term, but it does mean touching long-term issues and opportunities. It also means touching competitive things, things that make you different, things that make customers choose you over other people. Being strategic is as much about helping your company distinguish itself in the marketplace and continue to build and secure its future as it is about thinking several years out. And all of us need to have a line of sight to how we make our contributions that way. As an L&D professional, you can help your employees develop their strategic thinking skills by following the steps I outline below.
2. Know your company’s strategy
For anyone who’d like to develop their strategic thinking skills, it’s important to develop a strong grasp on your company’s strategy. Winning and competing are the fundamentals of strategy. Employees who want to familiarize themselves with their company’s strategy should know the following: What things has the company said are important? How has the company said it’s different from competitors? Why do customers choose your company and why do they believe your service or product is better than others?
If you or your employees don’t know those things, the first step is to understand the nature of your company’s strategy. Remember, it’s not just your mission statement or values statement — it’s how your company competes and makes money. Being more strategic is contextual — it’s about your company’s strategy, not just any strategy.
I also recommend that you and your employees learn how your organization is set up to compete and win in whatever field you’re competing in. Learn about your competitors, learn about the people who also do what your company does and why companies would choose them over you. See if you can identify why you’re losing customers to somebody you should be winning. Then you can dig in deeper to find out if your company is telling them the wrong story or if you are somehow deficient in your service or quality. Is there some feature that they really want that your competitor offers and you don’t?
A great place to start with this is anywhere your company has published a strategy or a strategic plan, which will likely include a set of objectives and goals for the year. Let employees know that if they can’t find it, their manager should be able to point them in the right direction. Then take the time to dive in deeper to learn more about what the work is. For example, if your company has said they’re going to invest in a new technology platform, go learn about it.
For the competitive analysis, you probably already have a number of subject matter experts on your sales, marketing, and customer success teams. Encourage your employees to seek out time with these people to get an overview of your company’s biggest competition and the most frequent complaints or requests they hear. If you want to be a more effective strategic thinker, knowing what to focus your thinking on is the first step.
3. Connect your work to the strategy
Understanding your company’s strategy is a great basis of knowledge. Once you or your employees have developed that, you can start to ask where you and your work fit. For anyone who’d like to do this, I recommend thinking not just about your specific role, but about your team and department. How do everyone’s capabilities and contributions work together?
Another tactic that helps with this is having one-on-one conversations with strategic people in your organization. You and your employees can offer to take people out for coffee and let them know that you’re interested in the company’s future and its work. Not only will these informational interviews help your team members better understand their roles, but they’ll help build their network within your company and learn what matters most to your organization. L&D teams can also facilitate this by inviting leaders to present on aspects of company strategy to smaller groups or holding lunch and learn sessions that encourage employees to ask questions and expand their understanding of strategic initiatives.
4. Voice your ideas
Once you and your team have an understanding and a basis of how your company competes and wins — or at least wants to compete and win — the next thing is deciding how you can voice ideas that matter. Find ways to offer your ideas, and encourage your employees to do the same.
If these opportunities don’t arise in someone’s current role, I recommend looking for ways to have closer visibility to the people who are more at the core of that work and getting involved. Be on the lookout for new assignments, projects, committees, task forces, or other opportunities to contribute.
The more strategically relevant someone is, the more important they’re seen to be. And that’s ultimately what we all want.
Your employees may find it’s hard to share their opinions when they’re getting involved in new areas, but sometimes the solutions to the toughest problems in the company come from the unlikeliest of places. I’ve heard countless stories where somebody on the periphery had a brilliant idea to solve a customer problem. Don’t ever assume that you or your role are so insignificant that you couldn’t offer a helpful idea. Develop your strategic thinking skills, and you could very easily have a suggestion that might lead to a really important solution or breakthrough. As an L&D leader, you can also help employees develop their public speaking and presentation skills to give them more confidence when speaking up.
And remember that strategic thinking has the power to help the organization on the whole, but it also helps the employees who engage in it. Better understanding your company’s strategy helps you more effectively prioritize your work and tasks so you can focus on the things that have the potential to make the greatest impact. Which will lead to you feeling the greatest satisfaction about your work.
A critical skill for developers of all experience levels is proficiency in GitHub. Github is a hosting platform for Git repositories that acts as a central location to store and manage code. GitHub is a popular choice for developers and their teams because it offers version control, collaboration capabilities, and a community of peers sharing their trials and successes in software engineering.
In this article, we’ll complete a tutorial on creating your first GitHub repository. First, let’s start with a closer look at the GitHub ecosystem and why I recommend students of my Web Developer Bootcamp course and all software developers take the time to understand this valuable tool.
GitHub vs. Git
They may have similar names, but GitHub is not synonymous with Git. Some developers work with Git and never use GitHub.
What’s Git? It’s an open-source version control management system that tracks changes to projects. Version control software records and manages every change made to source code and files. Git is a type of version control system for developers and teams to manage and collaborate on versions of code, which are stored in project repositories as it moves through the development life cycle.
Git can be used on its own without GitHub or other similar platforms, but it’s difficult to collaborate and share code with coworkers or the developer community without a platform like GitHub.
How does GitHub compare to Git? GitHub is a web platform that hosts Git repositories. Think of GitHub as a project viewer to share different code versions and access remote repositories. Each repository contains all project files and the code history. Repositories contain all project files, code history, and can have multiple collaborators.
Developers clone (download) a repository to their computer and work on a local version of the project. After working on code or developing new features on a local computer, developers push the changes to the same GitHub repository. Then, other developers or team members can download the version to their computer and stay synced with the project’s development.
5 GitHub benefits for developers
We know how GitHub differs from Git, but why should developers take the time to learn and use it? There are several benefits that I share with students on why they should use GitHub:
Collaboration — Collaboration with the developer community is one of GitHub’s most common uses, and it’s also one of its biggest benefits. It’s a way for teammates to work together and provide feedback. GitHub is also an ideal way for open-source projects to see continued collaboration from individual developers. In fact, GitHub is the largest open-source code repository on the internet!
Version control and backup — Git is the version control software, while GitHub is the platform where projects using Git are stored and accessed. Essentially, GitHub acts as the cloud backup to a software project.
Project management — GitHub can be used as a technical project management tool to track issues and bugs. This helps projects stay on schedule throughout the software development life cycle.
Developer portfolio — GitHub offers a free web hosting service called GitHub Pages. It’s a straightforward way to turn a GitHub repository into an easy-to-review portfolio website.
Networking — GitHub is a bit like a social networking website for developers. Users can follow each other, give project ratings, collaborate, communicate, and meet other developers from around the world.
How to create a GitHub repository
Now that you know the why of GitHub, I’ll get you started on the platform with this tutorial on creating your first repository. We’ll start by creating a local project to demonstrate how to upload it to GitHub.
Step 1: Create a new local Git repository
Open up your terminal and navigate to your projects folder, then run the following command to create a new project folder and navigate into it:
To initialize a new local Git repository we need to run the `git init` command:
After you run that command, you should get feedback that an empty Git repository was initialized for your project.
Step 2: Adding a new file to our Git repository
Create a new file in your project folder, we will call our sample file `hello.js`
You can use the graphical interface of your operating system to create the file, or use the following terminal commands:
Windows Powershell: ni hello.js Bash (Mac/Linux) terminal: touch hello.js
Save the file changes and switch back to your terminal window. Note: Make sure to use the `git status` command frequently when working with Git. It’s a great way to check the status of your project files and the whole repository.
Step 3: Making our initial commit to the local repository
Run the following commands to track your files and make the initial commit in the local repository:
git add .
git commit -m "Initial commit"
When that’s done, it means that we successfully prepared our new local repository to be pushed to GitHub!
Step 4: Creating a new GitHub repository
To create a new GitHub repository, navigate to github.com and press the plus symbol in the top right corner, then select the ‘New repository‘ option, as shown in the screenshot here:
You can also navigate to the GitHub page for creating new repositories by visiting this link: https://github.com/new
On that page, we first need to specify a Repository name and an optional Description.
For the Repository name, we can specify the same project name (hello-world) as the local repository that we are using in our example. If you want, you can also write a Description of your repository, but you can also skip that field as we did in the screenshot above.
You can set your repository to be Public or Private. When uploading your code to a public directory, make sure it doesn’t contain any sensitive data not intended to share with others. When creating a Private repository, you’ll manually choose who can access the new repository.
Step 5: Pushing our code to the GitHub repository
After the last step, you’ll be sent to the starting page of your new GitHub repository, which looks like this:
Since we’ve already created our Git repo locally, we’ll focus on the “…or push an existing repository from the command line” section of the page.
(Note: If we didn’t already have a local repository created, then we would follow the first set of commands to create a local repository from the remote GitHub one that was just created.)
The git remote add origin command will associate our local repository with the remote GitHub repository that we just created. We’re essentially telling your Git repo that we have a URL we want it to know about, and we give it the name “origin.” You do not have to name the remote “origin” but it is standard if you only have a single remote.
The git push command then pushes our local Git repository code to the remote GitHub repository.
Now, switch back to your local terminal and run the specified commands from your project folder:
When you run the git push command you’ll be prompted to enter your GitHub username and password, to log in to your GitHub account from the terminal.
After the repository is pushed, navigate back to your GitHub account page or the repository link and refresh it: https://github.com/<your-username>/<your-repo-name>
Now, you can use that link to share your project repository with other people!
Anyone can click on the hello.js file to see the contents of our project files. Also, other developers can clone or download the remote repository to their local computer by clicking on the green button highlighted in the screenshot. Other data, including past commits, existing branches, etc. will be visible from the repository.
Congratulations on creating your first GitHub repository! You’re ready to collaborate on open source projects, share with teammates, and learn more from the greater developer community. Now, learn more fundamentals of web development in my bootcamp course.
When people aren’t having fun, they seldom produce good work. That’s how David Ogilvy, the father of advertising, describes the relationship between people and their work. You might say I’m a little biased about this — when I was growing up, my family ran a number of independently owned toy stores throughout the San Francisco Bay Area. I began my career as an animator and story artist for The Simpsons and then moved on to Pixar, where I worked on films including Toy Story, Toy Story 2, Toy Story 3, Monsters Inc., Monsters University, Finding Nemo, UP, Cars, and Ratatouille. As one of the original story creators at Pixar, I participated in building and sustaining the creative culture from our early days as a startup to becoming the most successful filmmaking group in the history of Hollywood.
Here are my tips to build a culture of creativity and innovation at your organization.
1. Transform the physical environment
The physical workspace has the power to shape people’s attitudes and experiences. Steve Jobs had learned some important lessons during his time at Apple. He noticed that at Apple, people tended to lock themselves behind office doors all day — not a good environment for promoting community, innovation, and happiness. While giving people space and comfort might seem like a good thing, it ultimately led to them becoming more isolated and withdrawn.
When thinking about the workspace at Pixar, Jobs wanted to create a hub where everyone could run into each other, so the bathrooms, cafeteria, and building entrance were all located in one central place. When people left their offices during the workday, they would smile, say hello, and talk about what they were working on. The floor plan encouraged spontaneous creative moments and the cross-pollination of ideas.
And it wasn’t just the overall floor plan — people got creative with their personal spaces, too. People created tiki bars, cereal bars, and all kinds of other artistic installations. This meant people’s offices were conversation starters that expressed their personalities and kept them excited to come to work every day.
Even if you’re not ready to transform your entire office, setting up physical elements like furniture and fixtures also matters. You can start small. A rectangular table can create a pecking order — even subliminally. Round tables create the sense that everyone is on equal footing and all members have an equal say.
2. Eliminate the fear of failure: Failure and creativity go hand in hand
One of the keys to building a culture of creativity and innovation is eliminating the fear of failure. This can be a long and complicated process. Many people operate from a place of fear. They’re afraid to take chances, innovate, or be unique. This goes back to our childhoods when we discovered that doing something inventive or creative led to being picked on or bullied. We’re taught in school that if we don’t do things the “right” way, we’ll get an F. I was lucky that during my childhood, I was encouraged to be a misfit by my father. This led to me choosing environments like CalArts and Pixar where failure and creativity went hand in hand.
Unfortunately, for most people, the fear of failure they develop as children continues into adulthood. Many companies have built a culture ruled by fear where playing it safe replaces the impulse to take creative risks, and everyone is being too careful about what other employees or their bosses will think.
The most innovative environments are ones where people are encouraged to create, fail, and build new things. Great leaders have all had to fail hundreds of times before they became better leaders. By continuously testing and retesting ideas, they’ve made progress, and they bring that spirit to the companies they lead. Steve Jobs’ failures at earlier startups helped shape his later successes at Pixar and Apple (the second time around).
When leaders learn from their failures, they encourage others to fail so creativity can blossom. Companies like Google, Apple, and Pixar take chances, and as a result they become beacons for creative people. I look at Netflix today as a great example of this. You can see it in the content they’re developing — it’s original and pushes boundaries. It’s only possible to do this when you give people the freedom to experiment with different ideas.
Team leaders can also create an environment where it feels safe to fail. Rather than pitting team members against each other, they can encourage them to pursue a common goal. In the early days at Pixar, for example, if a story failed, then we weren’t going to have enough money to make the movie. Having a common goal reinforced the idea that we were all friends and shared a sense of camaraderie. It wasn’t a competition, so we were inspired to help each other succeed.
I have worked on numerous films and generated thousands of ideas that never made it to the screen. But these ideas and drawings often ended up inspiring others, linking up to previous ideas, or making a difference in some other way. If I had let these “failures” define me, I wouldn’t have kept going. Luckily, the work environment at Pixar taught me that this is all part of the creative process. When we were working on Toy Story, for example, the character of Woody was originally an unlikable jerk. Nobody who watched the early scenes liked him and The Disney Company decided they weren’t going to fund the movie because Woody was so unlikable. We learned from this failure and made changes so that Woody was more likable right from the start.
Another element of eliminating the fear of failure is creating clear lines of communication between leadership and employees and encouraging feedback on a regular basis. At Pixar, Steve Jobs and President Ed Catmull would rotate through the whole company, eating lunch with different people each day. During these conversations, they’d encourage people to ask them anything, creating an open environment where people felt empowered to share their ideas.
Feedback was also a regular part of the company culture. When you give feedback, I recommend being honest, but kind. Have a heart. Keep it brief — my rule of thumb is never give notes that are longer than the script you’re reviewing. Make sure that you deliver it in a timely fashion. If you wait too long, people may have already moved on to the next step. At Pixar we always gave our notes or feedback the same day we screened a film. It’s also important to suggest ways to make someone’s ideas better and ask questions to encourage reflection.
3. Encourage innovation
Everybody talks about innovation, but very few people or companies end up truly innovating. To innovate, you must be comfortable with failure time and time again (see the previous section!). Innovating is most often easier for startups because they have nothing to lose — no money, no name, no prestige. Startups are underdogs. They have a big advantage when they fight hard, and they can take the kind of risks that lead to innovation and success.
But this doesn’t mean that only startups can innovate. It just means more established companies will need to work a little harder to encourage innovation. It means you’ll need to focus on creating something new that people will want even before they know what it is. You’ll need to look at the world from a different perspective, discover unexpected obstacles, and solve them in unexpected ways. When you don’t keep surprising people with something new, they start to lose interest and even turn against you. The public may say they want more of the same, but they don’t always know what they want until you give it to them.
Sometimes creating the mindset shift you need for innovation to strike is as simple as getting out of the office and changing your surroundings. At Pixar, we’d go on research trips to learn more about the environment we were trying to create or better understand our characters.
But if you’re trying to spark innovation and creativity on an ongoing basis, it helps to recognize that people are more than the work they do on a day-to-day basis. Your employees have outside interests and passions, and rather than trying to compartmentalize them, you can encourage them to pursue these interests. For example, at Pixar we had educational stipends that we could use to get outside the walls of the office and pursue something that would refill us creatively, whether it was a painting class or attending an event like Comic-Con.
At the same time, we were encouraged to pursue our personal passions while we were at work, too. If we wanted to make our own film or comic book, we could do so and the company wouldn’t own the rights to it. Pixar encouraged these personal projects because they realized it fed into our creativity and innovation on the job.
You don’t have to overthink it — just look for ways to support your employees as they pursue their interests. At Pixar we’d go out for drinks and draw caricatures for a night. This was a fun way to let off steam and strengthen our friendship with our coworkers, and it ultimately spilled back into our work, too.
It all comes back to the quote I mentioned at the beginning — the work environment has a direct impact on the quality of work that people produce. If you want to encourage creativity and innovation, it’s important to imbue those qualities in your office layout, work practices, and values. And don’t forget to have fun while you’re at it!
It’s useful to understand TensorFlow’s place in the world of artificial intelligence, specifically why it’s considered a deep learning tool within the greater machine learning discipline.
Machine learning is a general approach that uses a variety of algorithms to extract insights out of data. As datasets grow, so do the complexities of the algorithms used to interpret that data. Algorithms built for small datasets may be able to tell the algorithm what to do in every possible scenario. But in large datasets with millions of data points, that simply isn’t realistic. Instead, machine learning techniques teach algorithms how to learn from the data they ingest and find insights from those learnings and trends.
A common machine learning example is found on real estate websites like Zillow to predict the listing price of a house. An algorithm ingests historic data on sales of houses in the area, including the number of bedrooms, bathrooms, cosmetic features, and more to then determine the likely value of the house.
Deep learning methods of artificial intelligence use artificial neural networks to accomplish tasks similar to those considered in machine learning. Due to their unique capabilities, deep learning methods can perform complex tasks that are impossible for typical machine learning algorithms. For example, deep learning neural networks can identify objects in images such as identifying a cat versus a dog in an uploaded image (a project we do in my course).
Neural networks accomplish these tasks because they are designed to mimic how the human brain’s biological neurons operate. Neurons work together to think, learn, process information, make decisions, etc. A neural network simulates a brain’s functionality by arranging artificial neurons into layers and connecting those layers. Artificial neurons (perceptrons) accept inputs and provide usable outputs through the use of an activation function.
4 important tools in the TensorFlow ecosystem
As TensorFlow adoption has grown, its user community has created an ecosystem of tools that solve a wide array of problems like the use of a specific programming language, easier data ingestion, or serving models to a customer. Some of the most useful tools include:
TensorBoard — Technically this is a separate library, but still part of the TensorFlow ecosystem. It’s an automated dashboard working in conjunction with TensorFlow to monitor how well your model is learning and adopting your dataset. It can also visualize a graph of your network so you can verify if it matches your intended design.
TensorFlow Lite — This light version of TensorFlow is used for deploying models on mobile or Internet of Things devices with much less processing power than a desktop or cloud computer. For example, TensorFlow Lite might be used for an app that identifies the nutritional information (typical caloric content, carbohydrates, etc.) based on an uploaded image of a plate of food.
Why TensorFlow over other deep learning libraries?
While quite a few deep learning libraries are used in industry and academia, TensorFlow is a solid choice for engineers of various expertise levels for several reasons:
Large community — TensorFlow is hugely popular in the deep learning community. You’ll find active online groups, frequent in-person meetup opportunities, and plenty of educational resources for you and your team.
Backed by Google — Google invested heavily in AI research in the last decade, which earned it AI and data science credibility across many of its products, including Google Cloud. It continues to resource TensorFlow’s development and open-source accessibility while also using it across many of its own commercial and enterprise products.
Tools ecosystem — Other deep learning libraries don’t have a robust ecosystem of tools like those we explored above. Many libraries began as a research method and weren’t fully intended for production use. Google’s prioritization of a production-ready product helped establish a strong community of enthusiasts who built related tools. Google also provides Google Colaboratory, a free tool for developers to write, run, and share code within Google Drive.
What’s new in TensorFlow 2.0?
TensorFlow was initially designed for advanced practitioners and was not easy for beginners. Its early version had a complicated static graph system requiring developers to define the entire graph in code before running models. TensorFlow 2.0 is now designed with usability in mind and is a great choice for students new to deep learning and offers a few fresh features including:
Keras integration — When TensorFlow first debuted, it used high-level APIs for user experimentation that were fairly complicated, especially for beginners. With the introduction of TensorFlow 2.0, the default API is now Keras. Keras is an easy-to-use high-level API that allows for simple and fast prototyping through user-friendliness, modularity, and extensibility. It fully supports both convolutional networks and recurrent networks, as well as combinations of the two. The TensorFlow 2.0 Keras API also runs seamlessly on CPU and GPU.
Eager execution by default — TensorFlow 2.0 executes eagerly (like Python normally does), meaning graphs and sessions should feel like implementation details. This makes the library much easier to use and makes debugging more straightforward.
Standardization — An engineer’s best friend, standardization aligns everything across the different versions of TensorFlow. If you save a Python TensorFlow model, you’ll have the ability to serve it across all the different ecosystem pieces. The goal is to have teams and developers write TensorFlow once in a single language like Python, but then execute it to any application.
TensorFlow applications and examples
One of the most popular examples of TensorFlow is called image classification, which trains a neural network to reliably identify which animal is in a photo, for example. But, TensorFlow has so many more applications than that relatively simple classification. We can understand more of TensorFlow’s real-world applications through the lens of their specific neural networks subcategories.
Artificial Neural Networks (ANN) — This type of neural network excels at supervised learning tasks including classification and regression models. A regression task could be the prediction of housing prices in a specific neighborhood, like the real estate website example we noted earlier. In our course, we take a look at real data from historical sales in the Seattle area and build a model to predict the sale price of future homes put on the market.
Classification models predict the category of something. In the course, we examine real data from LendingClub to predict whether or not a borrower will pay back their loan given historical feature information about the person.
Convolutional Neural Network (CNN) — Here, datasets are used to analyze images and video. A high-performing example is handwriting analysis, which has great accuracy thanks to MNIST, a database of handwritten digits and letters. Where can you see convolutional neural networks (CNNs) used most often? Your mailbox. CNN-powered machines can now interpret the handwriting on your holiday card envelope as good as or better than humans. CNNs are also now used as the basis for self-driving vehicles as they analyze camera images from vehicles. In the TensorFlow 2.0 course, you’ll work with real image files, such as identifying .jpg images of dogs.
Recurrent Neural Network — Another deep learning methodology where TensorFlow is applied is through the recurrent neural network (RNN). RNN excels at problems based on sequences such as predicting future sales based on historical sales data or estimating next season’s pumpkin yields through previous seasonal information. In my course, you will be learning how to forecast future sales data.
With TensorFlow 2.0’s updates making it easier to use for technical teams and engineers of all experience levels, this is a great time to start building neural networks and make your deep learning projects come to life. Start learning in my course Complete TensorFlow 2.0 and Keras Deep Learning Bootcamp.