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Advance into the future of tech with AgileFever’s AI and ML BootCamp, an elite, live training experience designed to help professionals transition into high-impact AI and ML roles. This isn’t a theory-heavy course. It’s a practical, 80-hours, 100% live-trainer-led program built for real-world implementation from day one.
Learn to build and deploy intelligent systems using tools like TensorFlow, PyTorch, Scikit-learn, Hugging Face, OpenCV, and more. From foundational statistics to deep learning, LLMs, NLP, and computer vision, you will work hands-on across the entire AI pipeline.
Every module is taught by top-tier instructors from FAANG and global tech firms, ensuring you don’t just learn AI, but practice it the way companies do with 15 real time projects.
This BootCamp is ideal for engineers, analysts, and developers looking to upskill with job-ready AI capabilities, real projects, and personalized career support.
80 hours of instructor-led training with hands-on labs and projects.
Gain the latest AI skills in Generative AI, prompt engineering, and much more.
Learn through a future-ready curriculum delivered live by FAANG experts, industry practitioners, and top university trainers worldwide.
Engage in 15+ hands-on projects to build a strong portfolio.
Covers Python, Machine Learning, Deep Learning, NLP, computer vision, and LLMs with real applications, not generic overviews.
Real-world projects covering domains like healthcare, fintech, and e-commerce, Insurance and Banking.
Work directly with TensorFlow, PyTorch, Scikit-learn, OpenCV, to build practical AI systems.
Evaluate and optimize models using precision, recall, F1 for classification, RMSE for regression, and GridSearchCV for cross-validation techniques.
Train models, track experiments, and prepare for production environments using real practices.
Ability to choose your capstone project from real-world use cases for tailored, goal-oriented learning.
Capstone project that simulates an end-to-end AI use case
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
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 Ensamble Methods
Naive Bayes
Support Vector Machine ( SVM)
k-Nearest Neighbors (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
ProjectLong short-term memory (LSTM)
Natural Language Processing Basics
To fast-track your career and achieve
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 AgileFever AI and ML Bootcamp is amazing! The teachers explain everything slowly and very clearly. The lessons are easy to follow, and there are lots of practice projects. It’s great for beginners because you don’t need to know much before you start. You learn how to use real tools for making AI. This bootcamp helped me understand AI easily and gave me skills for a job. I loved it and I think it’s the best place to learn AI and machine learning.
This course is AI- and ML-focused, not just data science. We go beyond analysis and dashboards — we teach you to build intelligent systems using ML, DL, NLP, LLMs, and MLOps. You’ll also learn deployment and production practices, which are often missing from generic data science courses.
Yes — we cover Deep Learning extensively using TensorFlow, Keras, and PyTorch. You’ll build real models like CNNs for face detection, RNNs and LSTMs for sequence prediction, and get a solid grounding in neural networks and optimization techniques.
No need to be an expert. We cover Python essentials for AI/ML, including NumPy, Pandas, Matplotlib, and object-oriented programming — all taught from scratch.
Yes — we have an entire module on NLP, including TF-IDF, topic modeling, and transformers, along with LLM use cases using ChatGPT, Hugging Face, and Gemini. You’ll also build your own chatbot project.
Yes. You’ll learn how to track experiments, train models, and move toward production, so you’re ready for real-world deployment. We cover model evaluation, explainability, ethics, and monitoring.
You’ll complete 15+ domain-based projects across Healthcare, Fintech, Retail, and more — plus a Capstone Project that simulates an end-to-end AI pipeline. You’ll graduate with a portfolio to showcase in interviews.
Absolutely. You’ll write code using TensorFlow, PyTorch, Scikit-learn, OpenCV, and other libraries. These aren’t demos — you’ll build and train models live, just like it’s done in real jobs.
We’ve had learners from various backgrounds. The curriculum starts with Python, statistics, and ML from scratch, and our live format ensures you get real-time help when needed. You just need basic logic and willingness to learn.
Yes — after the core AI/ML program, you can choose from advanced electives like:
Yes — our curriculum is project-heavy, and we focus on job-ready implementation. Many of our learners have taken freelance gigs, internship roles, or transitioned into full-time AI roles after completing this bootcamp.
