Collection of Free Courses to Learn Data Science, Data Engineering, Machine Learning, MLOps, and LLMOps - KDnuggets (2024)

Begin your data professional journey from the basics of statistics to building a production-grade AI application.

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Data has become a valuable asset for businesses, governments, and individuals in today's rapidly evolving digital landscape. With the rise of data science, machine learning, and artificial intelligence, there has never been a more exciting time to dive into these fields. In this blog, we'll introduce you to a collection of free courses that can help you learn and master various aspects of data science, data engineering, machine learning, MLOps, and LLMOps.

These courses are available for free on GitHub and have gained immense popularity among community members. The best part about this learning track is that it's entirely self-paced and community-based, allowing you to learn at your own pace and connect with like-minded individuals who share your passion for data.

The Data Science Undergraduate Program consists of essential courses in theory, mathematics, algorithms, statistics, data science tools, databases, and machine learning. The program aims to cover all the necessary and optional courses that can help learners master data science and prepare for their professional life.

The Data Science curriculum is designed for individuals who are self-motivated and want to achieve something significant in their lives. It offers a comprehensive undergraduate program in Data Science, providing access to courses from the most prestigious universities in the world.

If you want to become a professional data engineer, DataTalksClub is offering a 6-week bootcamp that you can enroll in now. The bootcamp has several modules and courses that will teach you various skills. By the end of the course, you will be able to work with GCP, Docker, Postgres, Terraform, Mage, BigQuery, Spark, and Kafka.

The Data Engineering bootcamp is designed to challenge and develop your skills while also providing you with practical experience through various projects.

Check out 10 GitHub Repositories to Master Machine Learning for accessing a range of resources, from beginner-friendly tutorials to advanced machine learning tools for productions.

The 10 repositories contains:

1. 12-week ML-For-Beginners program by Microsoft
2. Links to ML courses, tutorials, and lectures from Clatech, Stanford, and MIT.
3. Mathematics for machine learning
4. Deep Learning eBook.
5. Machine Learning Bootcamp.
6. List of Machine Learning Tutorials.
7. List awesome machine learning tools.
8. List of machine learning interviews.
9. Machine learning cheat sheets.
10. List of MLOps tools.

MLOps bootcamp from DataTalks.Club focuses on the practical aspects of productionizing machine learning services. The course is designed for data scientists, ML engineers, software engineers, and data engineers who are interested in learning how to deploy ML models into production.

The bootcamp consists of several modules that combine video lectures, practical exercises, homework assignments, and further reading materials to deepen understanding and application of the concepts. The aim of the course is to provide students with a strong foundation in MLOps, enabling them to effectively manage and deploy machine learning models in real-world scenarios.

The Large Language Model (LLM) course is a comprehensive program that will teach you the fundamentals of LLMs, train and fine-tune your own LLMs, and deploy them to production. Each core section covers a range of topics, supported by freely available online YouTube tutorials, guides, and resources.

The LLM course provides a structured approach to learning. It offers a range of resources, including tutorials, videos, notebooks, and articles, all available in one convenient GitHub repository.

This collection of free courses offers a wealth of resources for anyone looking to start their data science, data engineering, machine learning, MLOps, and LLMOps career. With courses covering theory, tools, examples, and real-world implementation, these self-paced career tracks have something valuable to offer both beginners and seasoned professionals.

Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master's degree in Technology Management and a bachelor's degree in Telecommunication Engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.