The initial launch of TensorFlow sparked a surge in Deep Learning architectures and solutions, due to its popularity as a framework for handling various artificial neural networks.

Data Engineers need more than just engineering skills; like software engineers, they possess a strong grasp of logic and its workings.

Data science has exploded as a practice in recent years, with open-source technologies such as Linux and Kubernetes playing a major role in driving innovation.

As the days get longer and the weather gets warmer, it's time to go out and search for the perfect lightweight Linux distro.

Open source software developers and engineers are in high demand. By focusing on training for the right certifications and specialty skill sets, individuals can take their careers in a range of directions.

MLOps is a set of strategies and techniques that allow data science teams to quickly and effectively create, deploy, and maintain ML models in production environments.

Developers need a reliable VPN service to protect their data and identity online and ensure secure browsing.

Now is the perfect time to build the Cloud DevOps skills you need for a rewarding career in tech.

Learning MLOps can give you valuable skills to develop and maintain ML/AI models more efficiently and effectively, making you more attractive to employers looking for data professionals with experience in this discipline.

The Managed Kubernetes Services from the leading organizations in the cloud computing ecosystem have all made huge strides over the past few years, enabling companies to run containerized workloads with cutting-edge open source capabilities.

There are rewarding career paths available if you have some TensorFlow experience under your belt! We’ve done the hard work and collated a list of resources that provide hands-on and project based learning.

Python has a design philosophy that emphasizes code readability, notably using significant white space. It is mostly used for developing web and software applications, automation, data science, and machine learning.

Building technical expertise and advanced skill-set will help you become a prolific data scientist.

To become a skilled UX Designer, you’ll want to focus on fundamentals, user research strategy, visual communication design, responsive design, and so forth.

It doesn’t take a rocket scientist to learn machine learning for finance. But it can feel like it if you’re just getting started on your own.

Become AWS certified and demonstrate your technical proficiency with an AWS certification.

So you’re thinking about Kubernetes certification. That’s great!

If you need to upgrade your skills but feel intimidated by statistics, don't panic. It's much easier to develop the foundational Statistical skills you need.

Linear Algebra is a vital cog in data scientists’ skill set that learners don't bother much about because they find maths intimidating.

Cloud security is a cornerstone of cloud computing. It is a brilliant career path that provides economic stability, and obtaining certification is the fundamental step.

Machine Learning Engineer is one of the most lucrative and dynamic career paths in Data Science and Ai.

Python is one of the most popular programming languages in the world. It is simple, elegant and easy to code with Python, which is why it has gained a colossal popularity in one decade.