Generative AI gets most of the attention, but a lot of the AI running inside companies is still classical machine learning: models that predict churn, flag fraud, forecast demand, or classify images. The AI and ML BootCamp teaches that foundation, from statistics and Python through machine learning, deep learning, computer vision, and NLP.
This guide covers what’s in the program, how it’s assessed, what it costs, and who should pick something else.
The AI and ML bootcamp at a glance
| Total hours | 80 |
| Length | 10 weeks, with cohorts on weekday evenings or weekends |
| Modules | 9 |
| Projects | 13+ domain projects in areas such as healthcare, fintech, and retail, plus a capstone |
| Tools | 11+, including Python, Pandas, scikit-learn, TensorFlow, Keras, PyTorch, and OpenCV |
| Capstone | Face mask detection with computer vision, or customer churn prediction |
| Assessment | Multiple-choice questions, projects during the program, and a final capstone |
| Current price | $1,600 (regular $2,000) or ₹85,000 (regular ₹1,00,000) |
Additional discounts are available. Contact us to know more.
How the nine modules are organized
The program spends a third of its modules on statistics and analytics before any model training. That’s unusual for a bootcamp, and it’s the right call: most mistakes in applied machine learning come from misreading data, not from choosing the wrong algorithm.
Number of modules in each part of the AI and ML BootCamp
Source: AgileFever AI and ML BootCamp curriculum, October 2026. Grouping is ours.
| Module | What it covers |
|---|---|
| Fundamentals of data analytics | Types of analytics, how AI, ML, deep learning, and data science differ, examples across industries |
| Statistics, basic and advanced | Sampling, central limit theorem, distributions, hypothesis testing, t-tests, ANOVA, chi-square, probability |
| Python essentials | Python from the ground up, Jupyter, NumPy, Pandas, and Matplotlib |
| Data science with Python | Exploratory analysis, cleaning, feature engineering, outliers, imbalanced data, scikit-learn |
| Supervised learning | Linear and logistic regression and other classification and regression algorithms, with evaluation using confusion matrices and ROC curves |
| Unsupervised learning | Hierarchical clustering, k-means, and PCA |
| Deep learning | Neural networks with TensorFlow and Keras, CNNs, image processing with OpenCV, RNNs and LSTMs |
| Natural language processing | Text preprocessing, TF-IDF, sentiment analysis, word embeddings, and topic models |
The capstone
You choose one of two. Face mask detection is a computer vision project built with a CNN and OpenCV. Customer churn prediction is a classic business ML problem: predicting which customers are likely to leave, using tabular data. If you’re aiming at product or analytics-heavy roles, churn is the more common interview topic. If you want to work on vision systems, choose face mask detection.
Do you need Python first?
No. Python, NumPy, Pandas, and core statistics are taught from scratch, and no prior data science experience is required. Some programming exposure makes the first weeks easier, though. The program moves through Python in one module, so if you’ve never coded, spend a few weekends on basic Python before the cohort starts. AgileFever’s 6-hour Python for AI course is one way to do that.
Who it’s for
The program lists ten typical transitions. Some of the most common:
| Your current role | Where it can lead |
|---|---|
| Data analyst | Machine learning engineer |
| Software or backend engineer | AI/ML engineer |
| Data engineer | ML engineer |
| Data scientist | Applied AI engineer |
| Recent graduate or final-year student | Junior AI/ML engineer |
Who should choose something else
- If you want to build LLM apps and AI agents, the GenAI and Agentic AI BootCamp is the direct route
- If you already train models and need to deploy and monitor them, take the MLOps BootCamp
- If you need a general understanding of AI rather than hands-on model building, The AI Blueprint takes 4 hours
The program describes itself as the natural foundation for the GenAI and MLOps bootcamps. That’s a reasonable order if you’re starting from scratch, but you don’t need all three. Pick the one that matches the job you want next.
Cost and dates
| Cohort | Dates |
|---|---|
| October | October 26, 2026 to January 7, 2027 (October 27 to January 8 for India) |
| November | November 28, 2026 to January 31, 2027 |
The current price is $1,600 in the US (regular $2,000) and ₹85,000 in India (regular ₹1,00,000). EMI options start from $66 a month. Check the program page for current dates and time zones.
Additional discounts are available. Contact us to know more.
FAQ
How is this different from a data science course?
It goes further into model building: deep learning, computer vision, and NLP. A typical data science course spends more time on analysis and dashboards.
Is there an exam?
Yes. Assessment combines multiple-choice questions, projects during the program, and the final capstone.
Does it cover generative AI?
Not as a focus. It covers the machine learning and deep learning foundations that generative AI builds on. For LLMs and agents, see the GenAI and Agentic AI BootCamp.
What to read next
For a general guide to choosing any machine learning program, read AI and Machine Learning Bootcamp: How to Choose the Right One. If you’re weighing bootcamps against other formats, see AI courses vs bootcamps.
