Written by the AgileFever editorial team. Program details were checked against the live program pages in October 2026. We run both programs and compare them here, so check the details against the program pages.
Both programs cost $1,600 in the US right now and both run for roughly two months or more, so price will not decide this. The first question is whether your work involves your own data and prediction, or language models and text.
The programs at a glance
| AI and ML BootCamp | Gen AI BootCamp | |
|---|---|---|
| Price (US) | $1,600 (regular price $2,000) | $1,600 |
| Length | 80 hours over 10 weeks | 72 hours over 9 weeks, as listed |
| Modules | 9 | 12 |
| Projects | 13+ across healthcare, fintech and retail | 9 plus 3 capstone options |
| Capstone | Computer vision or customer churn prediction | LegalBot, AI Tutor or Resume Screener |
| Starting point | The page says no prior Python or ML background is required | Python needed; the page contradicts itself, so confirm with an advisor |
| Core tools | Python, scikit-learn, TensorFlow, PyTorch, Keras, OpenCV, Pandas | LangChain, LlamaIndex, FAISS, Pinecone, Hugging Face, OpenAI APIs |
Additional discounts are available. Contact us to know more.
What you actually build
In the AI and ML BootCamp the first three modules are statistics and analytics: distributions, hypothesis testing, ANOVA, probability. Modules four and five cover Python for data science. After that you work through supervised learning, unsupervised learning, deep learning and NLP. Projects use real tabular, image and text data, and the capstone takes you from raw data to a working churn model or vision system.
In the Gen AI BootCamp you meet Python and deep learning briefly, then move to prompt design, working with the OpenAI, Claude and Gemini APIs, retrieval-augmented generation, LoRA and QLoRA fine-tuning, image generation, and deployment with Docker and Hugging Face Spaces. The capstone is a deployed application, not a trained model from scratch.
From the program pages, October 2026
Choose by the problem you want to solve
| If your work looks like this | Lean towards |
|---|---|
| Predicting churn, demand, fraud or risk from company data | AI and ML BootCamp |
| Reading images, such as defects, scans or faces | AI and ML BootCamp |
| Building a chatbot over internal documents | Gen AI BootCamp |
| Summarising, classifying or drafting text at scale | Gen AI BootCamp |
| You are a data analyst or engineer who wants a base to build on later | AI and ML BootCamp, then add a GenAI course |
| You already train models and want to move to LLM applications | Gen AI BootCamp |
Can you take both
Yes, and the order matters. Statistics and model evaluation carry over to LLM work: you cannot judge whether a fine-tuned model improved without them. People who start with the Gen AI BootCamp and skip the fundamentals often hit a wall when a retrieval system underperforms and they have no way to measure why. If you are new to data work, the AI and ML BootCamp first is the safer path. If you already have ML experience, go straight to generative AI.
What neither covers
- Neither is an agents course. For planning, memory and multi-agent systems, see the comparison with the GenAI and Agentic AI BootCamp.
- Neither is built around operating models at scale, which is the MLOps BootCamp’s job.
- Salary and job-growth figures on the program pages are market projections, not outcomes we can promise for you, so weigh them accordingly.
