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Kickstart Your Data Science Journey with These Essential Posts

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Chapter 1: Starting Your Data Science Learning Journey

As the new year begins, many individuals take significant steps and set ambitious goals. If you’re looking to embark on or continue your education in Data Science, this series of articles can help you find your way.

If you're a newcomer to this field, it can initially seem daunting due to its vastness. Data Science and Machine Learning consist of numerous branches, which can be intimidating at first.

Before diving in, it's essential to understand what you’re getting into. For a reality check, read "Why You Should Not Be a Data Scientist." Once you're ready to begin, recognizing the breadth of this field can make it challenging to determine what to focus on and where to start. A helpful resource is "Become a Machine Learning Engineer in 2022," which provides a list of foundational skills to acquire.

In addition, "Learn Data Science For Free" offers a comprehensive compilation of free courses and tutorials available online.

Section 1.1: Specialization is Key

When I began my journey, I discovered a strong interest in Computer Vision. If you find yourself in a similar position, "How To Start Learning Computer Vision in 2022" could serve as a beneficial starting point.

Data Science Learning Resources

Photo by Ian Schneider on Unsplash

Section 1.2: Staying Motivated

Persistence is crucial in this domain. Developing certain habits is essential, while others should be avoided. To help with this, consider reading "5 Habits Successful Data Scientists Should Master" and "4 Bad Habits a Data Scientist Should Avoid."

Section 1.3: Beyond the Notebooks

It’s vital to ensure that your models and personal projects don’t remain confined to notebooks, as that won’t be the case in a professional setting. There exists a broader world beyond those code cells, known as MLOps.

This topic is explored in a series that begins with "Introduction to MLOps" and concludes with "4 MLOps Tools To Deploy Your Machine Learning Model." The latter provides a comprehensive list of posts from the series.

Chapter 2: The End Goal

If you’re not pursuing this field purely as a hobby, you might be looking for ways to leverage your skills for employment, career transition, or supplementary income.

For insights on how to make an impression during job interviews, check out "How To Stand Out During Your Job Interviews" and "How Beginner Data Scientists Gain Experience."

The first video titled "Starting a Career in Data Science (10 Things I Wish I Knew…)" offers valuable tips and insights that can enhance your understanding of the field.

The second video, "How I Would Learn Data Science in 2023? (If I Could Start Over)," provides a fresh perspective on mastering Data Science in today’s landscape.

If you found this article useful, consider following me on Medium and visiting my website: alessandroai.com. You can also subscribe to the Artificialis newsletter for more insights.

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