Columbia University is Offering 2 AI Courses for Free
FREE ALERT!
〰️
Learn AI for free
〰️
FREE ALERT! 〰️ Learn AI for free 〰️
Grab These 2 Free AI Courses at Columbia University, While You Can
Columbia Plus: https://plus.columbia.edu/
I was browsing LinkedIn the other day when I came across two free AI courses from prestigious Columbia University. As someone who likes learning about practical AI, prompt engineering, and real-world applications of large language models, these courses peeked my interest. That is why I signed up. It's free anyway.
These are not just generic AI courses talking about trends and buzzwords. They seem built for people who actually want to learn usable skills. The two courses are Prompt Engineering & Programming with OpenAI and Building Customized LLMs with OpenAI, both offered through Columbia+ under Columbia Engineering. Both are online and both are organized into 2 modules with an estimated workload of about 4 to 5 hours per week.
Checkout or Sponsors
At Mise En Place Tech LLC, we partner with innovative, high-quality brands. Some links are affiliate links, meaning we may earn a commission at no extra cost to you. This never affects our recommendations—we only feature tools we truly believe in.
Course Syllabi
BUILDING CUSTOMIZED LLMs WITH OPENAI
Module 1 - RAG
Module 2 - Fine Tuning
PROMPT ENGINEERING & PROGRAMMING WITH OPENAI
Module 1 - Prompt Engineering
Module 2 - Programming with OpenAI
At the time I wrote this blog, both courses were listed at a regular price of $99. For a limited time, learners could enroll for free using the code SPRINGAI.
The first course, Prompt Engineering & Programming with OpenAI, looks like a strong fit for anyone who wants to go beyond casually using AI tools and actually understand how to guide large language models more effectively. It focuses on the fundamentals of prompt engineering and then moves into coding with the OpenAI API. It covers practical applications like text generation, document summarization, and image creation, which are exactly the kinds of skills that feel useful right now in real workplaces and projects
Remember to use this code: SPRINGAI
I like how hands-on it is. Throughout the course, I worked with zero-shot, one-shot, and few-shot prompting, connected directly to the OpenAI API, and built advanced workflows using libraries like LangChain and OpenAI. We also used Google Colab, the OpenAI API, and the DeepSeek API as core tools, so it wasn’t just about learning concepts; it was about actually building and experimenting with AI in a real coding environment.
The second course, Building Customized LLMs with OpenAI, ended up being the more advanced follow-up. It took students beyond basic prompting into adapting and deploying models for specialized use cases, with a strong focus on retrieval-augmented generation (RAG) and fine-tuning.
The structure was especially valuable: one module on RAG, another on fine-tuning, plus topics like vector search, synthetic data testing, text analytics, knowledge graphs, and embedding customized GPT models into web apps. It felt particularly relevant for technical professionals who need AI systems tailored to specific industries and data.
I am building a like-minded community, Follow me at @HishamDMacaraya
To sum up, the first course taught me how to work effectively with LLMs and build useful features, while the second taught me how to customize those systems for specific domains and business goals. Taken together, they formed a practical, applied AI learning path that strengthened real-world skills without feeling overly academic or abstract.
