Course Category
Google Rating
Professionals Upskilled
Live Cohorts Delivered
Enterprise Teams Trained
This AI & Machine Learning Bootcamp is designed for learners and professionals who want to move beyond understanding concepts and start building practical machine learning solutions.
You will learn how to work with real-world datasets, apply machine learning techniques, and build models for tasks such as prediction, classification, and data-driven decision-making using industry-standard tools and frameworks.
Unlike traditional courses that focus heavily on theory or isolated algorithms, this program emphasizes hands-on learning and real implementations — helping you understand how to handle data, train models, and apply machine learning in practical scenarios.
By the end of the program, you won’t just understand machine learning concepts — you’ll be able to build and apply machine learning models to solve real-world problems and create meaningful impact.
Build ML models from raw data to results - Clean, explore, and prepare real-world data, then build models for prediction, classification, and decision-making.
Train and optimize machine learning models - Apply supervised and unsupervised learning techniques and evaluate models using practical ML workflows.
Build deep learning systems that actually work - Use TensorFlow, PyTorch, and Keras to build neural networks for real AI applications.
Turn computer vision into working applications - Build image classification and face detection systems using CNNs and OpenCV.
Build AI applications with NLP - Work with text, sequence models, RNNs, LSTMs, and NLP to create practical applications such as chatbots.
Work with the tools used in AI/ML engineering - Build hands-on projects using Python, Scikit-learn, TensorFlow, PyTorch, Keras, OpenCV, Pandas, and more.
Build a portfolio across real-world AI use cases - Complete 13+ projects across areas such as healthcare, fintech, and retail, covering the full ML development journey.
Prove your skills with an end-to-end capstone - Choose a career-focused project in Computer Vision or Customer Churn Prediction and build it from development to a working solution.
Who This Is Built For
Prerequisite
Earlier in your career or a recent graduate? Build your fundamentals first with Python for AI (6 hrs) or The AI Blueprint — then fast-track into this bootcamp once you’re past the basics.
AI/ML Engineer Job Statistics
Projected AI & ML job growth by 2032
Increase in AI-related job postings Y-o-Y
AI & ML market growth by 2030
30–60% average salary jump after AI / ML upskilling
Data Analytics across Domains
What is Analytics?
Types of Analytics
AI vs ML vs DL vs DS
Lab
Introduction to statistics
Central Limit Theorem
Measures of Central Tendancies
Measures of Spread
Measuring Scales
Descriptive Statistics
Inferential Statistics
Lab
Types of Distribution
Hypothesis Testing
Statistical Tests
Analysis of Variance
Goodness of Fit test
Probability Theory for Data Analytics
Lab
Python Fundamentals and Programming
Data Handling with NumPy and Pandas
Data Visualization with MatplotLib
Advanced Data Visualization with Seaborn
Lab
Introduction To Data Science
End-to-End Data Science
Reading data from different Sources
Exploratory Data Analysis
Data Science: Data Cleaning Feature Engineering
Data Science Fundamentals
Lab
Regression and Classification Algorithms:
Logistics regression
Decision Trees and Ensemble Methods
Naive Bayes
Support Vector Machine ( SVM)
k-Nearest Neighbours (KNN)
Hierarchical Clustering
K Means
Principal Component Analysis(PCA)
Artificial Intelligence
Neural Networks using Tensors and Keras
Project: Convolutional Neural Networks (CNN)
Recurrent Neural Networks
Project: Long short-term memory (LSTM)
Natural Language Processing Basics
Build a real-time computer vision system that detects human faces and classifies whether a person is wearing a mask or not using CNNs and OpenCV with deployment as a live web application.
Develop a machine learning model to predict customer churn using real-world business data, identify key churn drivers and provide actionable insights for retention strategies.
The exam will be in Multiple Q and A with multiple projects throughout the training and a Final capstone project.
Having background of data science and experice in Python is recommended.
Learn directly from active hiring managers and industry leaders. Gain real insights, confidence, and visibility that go beyond the classroom.
Build interview confidence through real-world assessments, structured prep, and feedback from professionals who actually hire.
Optimize your resume, LinkedIn, and GitHub to attract recruiter attention and stand out in competitive hiring pipelines.
Get personalized coaching from industry veterans—covering interviews, communication, workplace presence, and career strategy.
The 80-hour AI & ML BootCamp struck the right balance between theory and serious hands-on practice, and the session timings fit perfectly alongside my work schedule. The trainer had a great way of breaking down complex math and coding — what once felt like a black box became clear through projects like building neural networks and data models. Even with 25 years in the industry, this gave me the depth and confidence I needed to step into AI.
Python & Statistics → Data Cleaning & EDA → Supervised Learning (Regression, Classification) → Unsupervised Learning (Clustering, PCA) → Model Evaluation & Optimization → Deep Learning (ANN, CNN, RNN, LSTM) → Computer Vision (OpenCV) → NLP & Chatbot Development → Capstone & Career Support
This bootcamp goes beyond analysis and dashboards. You’ll learn to build intelligent systems — training models, building neural networks, working with computer vision and NLP, and preparing for production. Data Science courses rarely go this deep into Deep Learning or model deployment.
No prior experience with Python or data science is required. We cover Python fundamentals — including NumPy, Pandas, Matplotlib, and core statistics — from scratch in Module 4. Basic logical thinking and a willingness to code are all you need to get started.
Yes. Cohorts run on weekday evenings or weekends, with flexible EMI options starting from $66/month — designed for engineers who are currently employed and learning alongside their jobs.
TensorFlow, PyTorch, Scikit-learn, OpenCV, Keras, NumPy, Pandas, Matplotlib, Seaborn, Jupyter, Anaconda, GitHub – 11+ tools in total, the same stack used in production AI/ML environments.
Yes. Deep Learning takes up an entire module — covering ANN, CNN, RNN, and LSTM using TensorFlow, Keras, and PyTorch. You’ll build a face detection system using CNN and OpenCV, which most bootcamps at this price never touch.
13+ domain-specific projects across Healthcare, Fintech, and Retail — including disease prediction, customer segmentation, sentiment analysis, and a working chatbot — plus a final Capstone.
You can choose between Face Mask Detection using Computer Vision or Customer Churn Prediction using ML — both built end to end, ready to present in interviews.
The exam will be in Multiple Q and A with multiple projects throughout the training and a Final capstone project.
Yes. This bootcamp is the natural foundation for AgileFever’s GenAI, Agentic AI, and MLOps bootcamps — giving you a clear specialisation path when you’re ready to go further.
