A Complete Collection of Data Science Free Courses – Part 2

The second part covers the list of Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Data Engineering, and MLOps.

A Complete Collection of Data Science Free Courses - Part 2
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Editor's note: For the full scope of the data science courses included in this 2-part series, please see A Complete Collection of Data Science Free Courses - Part 1.


Note: The Coursera courses mentioned in the blog can be audited for free, meaning that you have access to all the course content and can read and view it without any cost.


Machine Learning


Machine learning is the backbone of modern technology. Almost every big company in the world is trying to use it to get the most out of the data. 

By taking the free courses, you will learn about classification, regression, clustering, and reinforcement learning. Moreover, you will learn about feature engineering, advanced algorithms, and optimizing techniques.


Deep Learning


Deep learning is driving modern artificial intelligence technologies like ChatGPT. They use deep neural networks to process the data and come up with a prediction. 

By taking these courses, you will learn about advanced machine learning algorithms, preprocessing techniques, feature engineering, and neural network architectures. 

You will also learn various algorithms used in computer vision, NLP, forecasting, automatic speech recognition, generative art, and reinforcement learning.


Computer Vision


DALLE.2 and Stable Diffusion 2.0 are generative algorithms that use both computer vision and natural language processing techniques to come up with high-quality generative art. Computer vision is generally used for image classification, generation, segmentation, and object detection. 

You can start your computer vision engineer journey by learning OpeCV, Keras, and deep algorithms.  


Natural Language Processing (NLP)


I know we all are excited about the large language model ChatGPT and Bard AI, and to start your journey in becoming an AI engineer, you need to first master basic natural language processing tools and techniques. 

You will learn about spaCy, classification, vector space, probabilistic models, sequence models, and attention models. 


Data Engineering


My favorite subject and the backbone of every technology is data engineering. Without it, we will be sharing data through ineffective ways like excel sheets and CSV files. 

By taking the courses, you will learn about modern data tools for gathering, transforming, loading, processing, querying, and managing data so that it can be leveraged by data consumers for operations, and decision-making. Furthermore, you will also learn about workflow orchestration, data warehouse, analytics engineering, batch processing, and streaming.




Machine Learning Operations (MLOps) is a set of practices used to automate, manage, and monitor the machine learning lifecycle. MLOps is driven by software engineering best practices of DevOps. 

By taking these courses, you will learn to streamline the process of developing, experiment tracking, testing, deploying and maintaining machine learning models. Moreover, you will automate testing, data and model versioning, and model monitoring.




Some of the courses in the second part are simply gems. They are better than paid courses if you ask me. These courses are designed to prepare you for the modern world. You will be learning about the latest algorithms, techniques, software, and technologies. 

I will highly recommend you take DataTalksClub and fast.ai courses to start your machine learning and data engineering career. 

In the second part, we have looked at the top free courses on machine learning, deep learning, computer vision, natural language processing, data engineering, and MLOps. 

I hope you like my list, and if you have free course suggestions, please write them in the comment sections. Thank you.  

In the previous part, we have covered:

  1. Programming
  2. Web Scraping
  3. Statistics and Probability
  4. Data Analytics
  5. SQL
  6. Business Intelligence
  7. Time Series 

This is the 6th edition in the collection series, check out:

  1. The Complete Collection of Data Science Cheat Sheets – Part 1 and Part 2
  2. The Complete Collection of Data Repositories – Part 1 and Part 2
  3. The Complete Collection of Data Science Books – Part 1 and Part 2
  4. The Complete Collection of Data Science Interviews – Part 1 and Part 2

The Complete Collection of Data Science Projects – Part 1 and Part 2
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.