The Top 3 Skills Developers Need for the Next Decade
As we move into the mid 2020s and beyond, we can expect to see some major changes in the world of technology. With that in mind, it’s important to make sure that your developers are equipped with the skills they’ll need to thrive in this rapidly changing landscape. Here are three skills that every developer should have in their toolkit over the next decade.
Summary
Skill 1: Learn New Languages Quickly
- Books: Quick and deep learning.
- Other Resources: Anki app lets you create free lists to practice daily. Great for on the go reinforcement.
- Books: Cloud computing, Devops with Kubernetes, Cloud Security, Cloud Cost Management
- Resources: A Cloud Guru offers a dedicated environment for practicing and learning practical devops skills. It’s how I leveled up to do DevOps work with confidence.
Skill 3: AI and Machine Learning Skills
- Books:
- Probabilistic Machine Learning, AI book for beginners which is actually understandable :)
- AI Pipelines with Spark, Data Lakehouses
- Python with Tensforflow V2 - Resources:
Coursera’s Deep Learning class and machine learning courses are useful to get started.
1. The Ability to Learn New Languages Quickly
Gone are the days when a developer could learn one programming language and be set for life. These days, new languages are being developed all the time, and developers need to be able to learn them quickly in order to keep up with the latest trends. Furthermore, being able to learn new languages quickly will also make it easier for developers to pick up related technologies, such as frameworks and libraries.
Don’t move on until you master the basics
When learning a programming language, it is important to first master the basic concepts. Once you understand why something works end to end, you can then move on to more advanced topics. However, if you try to skip ahead without a solid foundation, you will likely find yourself lost and frustrated. It can be tempting to want to move on to the latest and greatest features of a language, but resist the urge and take the time to understand the basics first. In the long run, you will be glad you did.
Spaced Repetition Quizzes
Spaced Repetition Quizzes (SRQs) are an effective way to learn and master new content. They work by spacing out quiz intervals so that you review the material just before you forget it. This spaced interval allows you to learn the material more effectively and retain it for a longer period of time. SRQs have been proven to be more effective than traditional quizzes, making them an excellent choice for anyone looking to learn a new programming language or tool. When using SRQs, be sure to create quizzes that cover all of the key concepts you need to learn.SRQs can also be used to assess your understanding of existing content. By taking a quiz on material you already know, you can gauge your understanding of the material and identify any gaps in your knowledge. This can be especially helpful when preparing for exams or job interviews. Whether you’re looking to learn something new or assess your existing knowledge, spaced repetition quizzes are an excellent way to do it.
Get Started
Here’s a great book that helps you build the meta-skill of learning
2. Cloud Computing Skills
Cloud computing is revolutionizing the way businesses operate, and it’s only going to become more ubiquitous in the years to come. As a result, developers who want to stay ahead of the curve will need to build up their cloud computing skills. Fortunately, there are plenty of resources available to help developers get up to speed on this rapidly evolving technology.
Cloud Orchestration
Containers provide a way to package up an application and its dependencies in such a way that it can run anywhere. This means no native access for storage or networking, which are handled through orchestration tools like Google’s Kubernetes service (which also takes care of managing high availability). Container platforms automate tasks involved with launching containers on hosts — including configuration management; scheduling resources at appropriate times based upon demand patterns expected from customer traffic generation rates combined with desired resilience measures set forth during deployment phases — all while monitoring workload sizes constantly so they know when scaling needs occur due either increased performance.
There are other competitors to Kubernetes including Nomad. HashiCorp’s Nomad is a simple and flexible workload orchestration tool that facilitates the deployment, management as well as scaling of different types on platforms such has On-premises or Cloud. It provides common pool infrastructure from multiple providers — both in terms if location (i e Locally) but also when it comes to type; this includes everything ranging bin packing containers for greater efficiency.
Learn more!
Cloud computing, Devops with Kubernetes.
Cloud Networking And Security
As businesses increasingly move data and applications to the cloud, they must also ensure that this transition is secure. Cloud networking and security helps to protect data and systems from unauthorized access, while also providing secure egress and ingress points for authorized users. In order to secure data in the cloud, businesses must first understand the shared responsibility model of cloud security. Under this model, the cloud provider is responsible for securing the infrastructure, while the customer is responsible for securing their data and applications. This means that businesses must implement their own security measures, such as encryption and access control. They must also carefully monitor activity in their cloud environment and be prepared to respond quickly to any threats. By taking these steps, businesses can secure their data in the cloud and ensure that their transition to the cloud is successful.
Getting Started
But this field is very deep, and I would recommend you follow up by reading this: Cloud Security.
Cloud Cost management
Cloud cost management is the process of monitoring, analyzing and optimizing cloud computing expenses. It’s a type of financial operation (finops) specifically for organizations that use cloud services. Because cloud services are charged based on usage, it’s important for companies to closely observe their costs and find ways to reduce them where possible. Rising costs can be caused by a number of factors, including sudden spikes in usage, changes in pricing plans, or inefficient resource utilization. By constantly monitoring costs and taking proactive measures to prevent wasteful spending, finops teams can help organizations keep their cloud budgets under control.
Get Started
This book is great Cloud Cost Management. And other resources here.
3. AI and Machine Learning Skills
Artificial intelligence (AI) and machine learning are two other technologies that are rapidly gaining traction in the business world. As these technologies become more commonplace, developers who have experience with them will be in high demand. Luckily, there are many online courses and tutorials that can help developers get started with AI and machine learning.
Deep Learning: Convolutional Neural Networks etc
Deep learning is a subset of machine learning that is concerned with algorithms inspired by the structure and function of the brain. Deep learning is Usually used to refer to the use of neural networks, which are a specific set of algorithms. Neural networks were inspired by our understanding of the brain and how it learns.
These algorithms are designed to learn in a similar way to the brain. Convolutional Neural Networks (CNNs) are a type of Deep Learning algorithm that are very effective in image recognition tasks. CNNs have been successful in identifying faces, objects, and traffic signs amidst other computer vision tasks.
However, more recently, there has been a shift towards using more complex models such as Generative Adversarial Networks (GANs). GANs are made up of two neural networks: a generator network and a discriminator network.
The generator network creates images that look realistic, while the discriminator network tries to identify which images are real and which ones are fake. The two networks then compete with each other, leading to the generated images becoming increasingly realistic over time. These more complex deep learning models are beginning to be used more frequently as they provide better results than traditional CNNs.
Want to really learn how it all works? This book actually makes AI and deep learning understandable for beginners. Udemy also has some really well rated courses to help.
Practical skills with Python Tensorflow2
Python is a programming language with many features that make it well suited for learning AI. For example, it has a large and active community that has created many helpful libraries. Additionally, Python is relatively easy to learn, even for beginners. TensorFlow 2 is a popular open source library for machine learning that can be used with Python. It allows developers to build complex AI models with ease. Together, Python and TensorFlow 2 provide everything you need to get started with learning AI.
Get started:
Great resource with indepth examples here: Python with Tensforflow V2
Learn how to work with Spark for AI Modeling Pipelines
Spark is an essential tool for those working with AI model pipelines. It allows for the construction of data lakes which are repositories of all the data used in training and testing a machine learning model. Spark also helps to manage and monitor the training process, ensuring that models are tuned correctly and that performance is optimal. In addition, Spark can be used to deploy a trained model into a production environment. As such, it is a critical tool for anyone working with AI model pipelines. Spark offers a number of advantages, including ease of use, flexibility, and scalability. As more and more organizations adopt AI technologies, Spark is likely to become even more essential.
Get Started
Here’s a great resource to get started: AI Pipelines with Spark, Data Lakes.
Prepare for the skills of the next century today!
The world of technology is constantly changing, and developers need to change with it if they want to stay ahead of the curve. In order to do that, they need to equip themselves with the right skills. Over the next decade, we predict that three of the most important skills for developers will be the ability to learn new languages quickly, cloud computing skills, and AI/machine learning skills.
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