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The field of data science is growing rapidly, and there’s a wealth of resources available to help you learn the skills you need to succeed. Whether you’re a complete beginner or a seasoned professional, there’s something out there for everyone.

In this post, we’ll explore a range of resources to help you on your data science journey, from beginner-friendly tutorials to advanced courses and curated collections.

For Beginners:

• Data Scientist Roadmap(Link):This GitHub repository provides a clear roadmap to help you navigate the vast world of data science. It outlines the essential skills and topics you’ll need to master, along with helpful resources.
• Learn Data Science(Link):This open-source resource offers a comprehensive introduction to data science. It covers the fundamentals of data science, including what it is and why it’s important. You’ll also find details on the topics covered and the datasets used in the learning path.

Expand Your Python Skills:

• Awesome Python(Link):This curated list of Python libraries and frameworks is a valuable resource for data scientists of all levels. Explore libraries for data analysis, machine learning, web development, database interaction, and more.

Deep Dive into Data Science with Python:

• Data Science in Python(Link):This collection of Python resources for data science delves into libraries, tools, and references for various tasks. You’ll find resources for data cleaning, manipulation, feature selection, dimensionality reduction, and more.
• DS Python Notebooks(Link):Get hands-on with data science using these Python notebooks. Explore libraries like TensorFlow, Theano, Keras, scikit-learn, pandas, NumPy, and matplotlib. The notebooks also cover big data tools like Spark and Hadoop.

Explore the Broader World of Data Science:

• Awesome Data Science(Link): This GitHub repository is a treasure trove of data science resources. It covers a wide range of topics, from the basics of data science to how to become a data scientist. You’ll also find links to online courses, tutorials, and more.
• Self Taught DS(Link):If you’re looking to embark on a self-taught data science journey, this free curriculum is a great place to start. It outlines a path of courses to follow, including prerequisites, and covers essential concepts like statistics, probability, and machine learning.

Sharpen Your Skills with Time Series Forecasting:

• Microsoft Time Series Forecasting(Link): Look no further than the Microsoft Time Series Forecasting resource. This awesome repository dives into practical forecasting techniques, helping you choose the best models and methodologies for your specific data. It even includes Python and R examples, perfect for data scientists and machine learning engineers.

Become a Master of Data Science:

• Data Science Masters Curriculum(Link): If you feeling ambitious, then check out the Data Science Masters Curriculum. This open-source curriculum lays out a comprehensive learning path, taking you from data science fundamentals to specialized areas. You’ll even get to tackle a capstone project to solidify your knowledge. Remember, data science is constantly evolving, and this curriculum reflects that, keeping you on the cutting edge.

Level Up Your Pandas Expertise:

• Pandas Exercises(Link): Pandas is a fundamental tool for data wrangling. Take your pandas skills to the next level with Pandas Exercises! This repository provides a structured approach to learning pandas with practical exercises. Test your understanding with solutions (both with and without code) to solidify your knowledge and become a pandas pro.

Explore a Treasure Trove of Data Science Resources:

• Best Data Science Resources(Link): If you Want to accelerate your learning, then check out Best Data Science Resources. This curated collection of free resources is a goldmine! Discover high-quality YouTube playlists, cheat sheets, and materials covering a wide range of topics, including machine learning, natural language processing, and statistics.

Become a Data Engineering Pro:

• Data Engineering How-To(Link): Thinking about making the leap to data engineering? Data Engineering How-To is your guide! This resource dives into what data engineering entails and provides a roadmap to success. It includes websites, books, courses, and communities to equip you with the knowledge and skills you need.

Expand Your Data Engineering Toolkit:

• Awesome Data Engineering(Link):  Explore the vast landscape of data engineering tools with Awesome Data Engineering. This GitHub repository is a one-stop shop for everything from databases (relational, NoSQL, graph, time series) to data ingestion tools and file systems. Find the perfect tools for your specific project needs.

Keep in mind:

• This list just scratches the surface of what’s available. There are many other great data science resources out there.
• The best resources for you will depend on your learning style and experience level.
• Don’t be afraid to experiment and find what works best for you.