MIT Applied AI & Data Science Program – completed 🥳

Finally done! 🥳

I still remember my first in-depth conversation about AI and LLMs. I was curious about the academic foundations and the science behind them. A friend of mine, AI expert Bilel SAID, told me back then: “Start with Andrew Ng's articles.”

That conversation triggered something. I didn't just want to use AI – I wanted to truly understand it, from mathematics to Generative AI.

The Search for the Right Program

Initially, I considered starting a full-fledged Master's degree. I was looking for something:

• Structured
• Demanding
• Comprehensive
• With real depth

Most certifications I found were either too short, too expensive, or too specialized (only ML, only Prompt Engineering, only Agentic AI etc.). Nothing covered the complete picture.

Until I came across the MIT Applied Data Science Program:

• 6+ months
• At least 12 hours per week
• Solid academic foundations
• Practice-oriented focus
• Reasonable investment

What We Learned

📌 Mathematics

• Statistics
• Probability Theory

📌 Data Science

• Python (NumPy & Pandas)
• Data Visualization
• Data Analysis
• Statistical Inference
• Clustering
• PCA

📌 Machine Learning

• Supervised Learning
• Unsupervised Learning

📌 Practical Data Science

• Decision Trees
• Random Forests (Bagging & Bootstrapping)
• Time Series

📌 Recommendation Systems

📌 Deep Learning

• ANN
• CNN (Vision AI)

📌 Generative AI

• Transformer Architecture
• RAG
• RLHF
• Prompt Engineering
• Agentic AI

Hands-on Instead of Just Theory

Every topic was hands-on. We primarily worked with Google Colab, building and testing models directly — no heavy local setup, easy collaboration.

And we had to complete two major practical projects:

🔹 Midterm – Deep Learning (CNNs)

Built and compared several models for digit recognition in images.

🔹 Final Project – Generative AI & Prompt Engineering (Zero-shot, Few-shot, and Chain-of-Thought Prompting)

Using the OpenAI API:

• respond to customer reviews
• perform sentiment detection
• generate retail insights

What I'm Taking Away

Today, I am proud to have completed the program. But more importantly:

I now have a structured, end-to-end understanding of AI, from mathematical foundations to real-world GenAI applications.

If you're considering a similar path or have questions about the program, feel free to reach out. You can find the link to the program here.

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On to the next challenge 🚀