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Learning from free courses can be very beneficial for those looking to pursue a career in data science. Free courses offer many benefits such as cost-effectiveness, flexibility, access to the latest tools and concepts, the opportunity to learn from industry experts, community support, and a hands-on learning experience instead of spoon-feeding.
In this blog, my goal is to facilitate you improve your data science skills by providing an extensive list of free courses on a variety of topics including Python, SQL, Data Analytics, Business Analytics, Data Engineering, Machine Learning, Deep Learning, Generative Artificial Intelligence , and MLOps.
Most of these courses come from top universities and platforms such as Coursera, MIT, UC Davis, FreeCodeCamp, Google, Microsoft, IBM, Harvard, and Stanford University. So start your journey to becoming a professional data scientist today!
Note: Coursera courses are available for free auditing, and if this option is not available, you can complete the courses on a trial basis or request financial aid.
Python is an crucial programming language for data science. You will learn how to manipulate data, analyze, visualize and machine learn. It offers a wide range of libraries and frameworks that simplify complicated tasks, making it a popular choice among data scientists.
SQL (Structured Query Language) is a query language used to manage and manipulate relational databases, which are key to storing, retrieving, and analyzing data.
As you probably know, data analytics is a key aspect of data analytics that helps companies make informed decisions based on data-driven insights. This involves using a variety of tools and techniques to extract meaningful information from data.
You can operate business intelligence tools like Power BI or Tableau to transform raw data into actionable insights that facilitate you make decisions. You don’t need to learn any programming languages other than SQL.
Data engineering is a subfield of data science that deals with designing, building, and maintaining data pipelines and infrastructure.
Machine learning is a field of artificial intelligence that involves creating algorithms that can learn from data and make predictions. This is an crucial skill for a data analyst.
Deep learning is a subset of machine learning that focuses on neural networks that consist of multiple layers. It is widely used in image and speech recognition, natural language processing and other complicated tasks.
Generative AI refers to the process of creating modern content, such as text, images and audio, by analyzing patterns and structures learned from existing data. During your learning process, you will mainly focus on multi-language models and how to train, tune, and deploy them.
MLOps, tiny for Machine Learning Operations, is the process of automating and streamlining the deployment and management of machine learning models. It is currently one of the most sought-after career fields in the data science industry.
- Python basics for MLOps by Duke University
- MLOps for beginners via Udemy
- Specialization: Machine Learning Engineering for Manufacturing (MLops). by DeepLearning.AI
- MLOps Bootcamp with DataTalks.Club
- Made of ML by Goku Mohandas
You don’t have to search Google to find high-quality data courses. All you need to do is bookmark this page and start your Python and SQL adventure. In a few months you will be able to receive, process, analyze and model data. After that, it will be a continuous learning journey. If you want to get hired by the best recruiters, it is highly recommended to build your portfolio from the beginning on GitHub or another platform.
Check out the blog “5 Free Platforms to Build a Strong Data Science Portfolio” to learn about other platforms and what they have to offer.
Abid Ali Awan (@1abidaliawan) is a certified data science professional who loves building machine learning models. Currently, he focuses on creating content and writing technical blogs about machine learning and data science technologies. Abid holds a Master’s degree in Technology Management and a Bachelor’s degree in Telecommunications Engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.