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AI CREATOR BOOTCAMP

Name: AI CREATOR BOOTCAMP
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This intensive 1-month bootcamp transforms engineering graduates into hands-on AI creators. The curriculum is structured around four progressive themes — Foundations, Language Model Ownership, Agentic AI Systems, and Production Deployment. Participants train their own Small Language Models (SLMs), build AI agents, develop dashboards, and ship a complete AI product by the end of the program.

Four Weeks

Enroll Now ₹24,990~~₹36,990~~

Highlights

Industry-grade curriculum updated quarterly
Real production-style projects
1-on-1 mentor support
Career counselling & resume reviews
Mock interviews with hiring partners
Lifetime access to course materials

Learning Outcomes

Build real projects you can showcase in interviews
Apply industry tools and workflows confidently
Understand core concepts through hands-on practice
Earn a certificate on successful completion

Introduction to AI, ML & Deep Learning — Landscape, Applications & Career Paths4h
- Mapping AI use cases across industries; Environment setup (Python, Colab/Kaggle)
Python Ecosystem for AI — NumPy, Pandas, Matplotlib, Seaborn2h
- Data manipulation, EDA, and visualization hands-on
Mathematical Foundations I — Vectors, Matrices, Linear Algebra2h
- Implement matrix operations and transformations with NumPy
Mathematical Foundations II — Probability, Distributions, Optimization Basics2h
- Probability simulations and distribution visualization
Data Preprocessing & Feature Engineering — Cleaning, Encoding, Normalization, Splitting2h
- Full preprocessing pipeline on Titanic / Churn dataset
Supervised Learning — Regression & Classification Algorithms2h
- Train Linear Regression, Logistic Regression, Decision Tree, Random Forest, XGBoost
Unsupervised Learning + Model Evaluation — K-Means, PCA, Confusion Matrix, F1, AUC2h
- Compare ML models and visualize feature importance

Neural Network Fundamentals — Perceptron, Activation Functions, Loss, Backpropagation2h
- Build a simple MLP from scratch using PyTorch
Training Deep Neural Networks — Gradient Descent, Regularization, Dropout, Batch Norm2h
- Visualize learning curves and prevent overfitting
Convolutional Neural Networks (CNN) — Architecture, Filters, Pooling, Transfer Learning2h
- Image classification using ResNet/VGG on a custom image set
Generative Models — GANs: Architecture, Training Dynamics, Use Cases2h
- Train a simple GAN for image generation
NLP Fundamentals — Tokenization, Bag-of Words, TF-IDF, Sentiment Analysis2h
- Build a text classifier using classical NLP features
Sequence Models — RNN, LSTM: Architecture and Training2h
- Sequence prediction on time-series or text data
Transformer Architecture — Self-Attention, Positional Encoding, BERT/GPT Overview4h
- Explore attention patterns; use pre-trained BERT for classification

LLM vs SLM — Understanding Scale, Trade offs & the SLM Ecosystem (Phi-3, Mistral 7B, Gemma, TinyLlama)4h
- Benchmark and compare 3 SLMs on a domain task
Custom Dataset Creation — Web Scraping, Annotation, Synthetic Generation, JSONL Format2h
- Build a domain-specific instruction-output dataset
SLM Fine-tuning with LoRA & QLoRA — PEFT, Hugging Face Trainer API2h
- Fine-tune Phi-3 Mini / TinyLlama on custom dataset
Evaluation of Fine-tuned SLMs — BLEU, ROUGE, Perplexity, Human Eval2h
- Run evaluation pipeline and compare base vs fine tuned model
Instruction Tuning & DPO — Direct Preference Optimization, Alignment Basics2h
- Apply DPO on a preference dataset
Model Serving with Ollama — Local Inference, API Wrapping2h
- Serve fine-tuned SLM locally using Ollama
SLM Project Day — Dataset Finalization + Full Fine-tune Pipeline8h
- Full supervised fine tuning run with logging on W&B

AI Agents — Architecture, ReAct, Tool Use, Memory & Planning4h
- Build a research agent using LangChain tools
RAG Systems — Vector Databases, Embeddings, ChromaDB / FAISS2h
- Build a document Q&A system over a domain knowledge base
Multi-Agent Systems — CrewAI / AutoGen: Roles, Orchestration, Evaluation2h
- Build a 3-agent pipeline: researcher + analyst + reporter
AI Dashboard Development — Streamlit / Gradio: UI, State, File Upload, API Integration2h
- Build a multi-page Streamlit dashboard for your SLM + agent
Production Deployment — FastAPI Backend, Docker Containerization, Hugging Face Spaces2h
- Containerize and deploy AI app with a REST API
Responsible AI — Hallucinations, Bias, Safety Red-teaming, Prompt Injection Defense4h
- Audit your own model for bias and safety issues
Capstone Project — Final Build, Polish & Demo Preparation8h
- End-to-end integration: SLM + Agent + Dashboard + Deployment

Mr. ABC

Professor

Ready to start AI CREATOR BOOTCAMP ?

Talk to a counselor and find out which batch fits your schedule and goals.

Enroll Now Back to Courses

AI CREATOR BOOTCAMP

Four Weeks

Enroll Now ₹24,990~~₹36,990~~

Highlights

Industry-grade curriculum updated quarterly
Real production-style projects
1-on-1 mentor support
Career counselling & resume reviews
Mock interviews with hiring partners
Lifetime access to course materials

Learning Outcomes

Build real projects you can showcase in interviews
Apply industry tools and workflows confidently
Understand core concepts through hands-on practice
Earn a certificate on successful completion

Introduction to AI, ML & Deep Learning — Landscape, Applications & Career Paths4h
- Mapping AI use cases across industries; Environment setup (Python, Colab/Kaggle)
Python Ecosystem for AI — NumPy, Pandas, Matplotlib, Seaborn2h
- Data manipulation, EDA, and visualization hands-on
Mathematical Foundations I — Vectors, Matrices, Linear Algebra2h
- Implement matrix operations and transformations with NumPy
Mathematical Foundations II — Probability, Distributions, Optimization Basics2h
- Probability simulations and distribution visualization
Data Preprocessing & Feature Engineering — Cleaning, Encoding, Normalization, Splitting2h
- Full preprocessing pipeline on Titanic / Churn dataset
Supervised Learning — Regression & Classification Algorithms2h
- Train Linear Regression, Logistic Regression, Decision Tree, Random Forest, XGBoost
Unsupervised Learning + Model Evaluation — K-Means, PCA, Confusion Matrix, F1, AUC2h
- Compare ML models and visualize feature importance

Neural Network Fundamentals — Perceptron, Activation Functions, Loss, Backpropagation2h
- Build a simple MLP from scratch using PyTorch
Training Deep Neural Networks — Gradient Descent, Regularization, Dropout, Batch Norm2h
- Visualize learning curves and prevent overfitting
Convolutional Neural Networks (CNN) — Architecture, Filters, Pooling, Transfer Learning2h
- Image classification using ResNet/VGG on a custom image set
Generative Models — GANs: Architecture, Training Dynamics, Use Cases2h
- Train a simple GAN for image generation
NLP Fundamentals — Tokenization, Bag-of Words, TF-IDF, Sentiment Analysis2h
- Build a text classifier using classical NLP features
Sequence Models — RNN, LSTM: Architecture and Training2h
- Sequence prediction on time-series or text data
Transformer Architecture — Self-Attention, Positional Encoding, BERT/GPT Overview4h
- Explore attention patterns; use pre-trained BERT for classification

LLM vs SLM — Understanding Scale, Trade offs & the SLM Ecosystem (Phi-3, Mistral 7B, Gemma, TinyLlama)4h
- Benchmark and compare 3 SLMs on a domain task
Custom Dataset Creation — Web Scraping, Annotation, Synthetic Generation, JSONL Format2h
- Build a domain-specific instruction-output dataset
SLM Fine-tuning with LoRA & QLoRA — PEFT, Hugging Face Trainer API2h
- Fine-tune Phi-3 Mini / TinyLlama on custom dataset
Evaluation of Fine-tuned SLMs — BLEU, ROUGE, Perplexity, Human Eval2h
- Run evaluation pipeline and compare base vs fine tuned model
Instruction Tuning & DPO — Direct Preference Optimization, Alignment Basics2h
- Apply DPO on a preference dataset
Model Serving with Ollama — Local Inference, API Wrapping2h
- Serve fine-tuned SLM locally using Ollama
SLM Project Day — Dataset Finalization + Full Fine-tune Pipeline8h
- Full supervised fine tuning run with logging on W&B

AI Agents — Architecture, ReAct, Tool Use, Memory & Planning4h
- Build a research agent using LangChain tools
RAG Systems — Vector Databases, Embeddings, ChromaDB / FAISS2h
- Build a document Q&A system over a domain knowledge base
Multi-Agent Systems — CrewAI / AutoGen: Roles, Orchestration, Evaluation2h
- Build a 3-agent pipeline: researcher + analyst + reporter
AI Dashboard Development — Streamlit / Gradio: UI, State, File Upload, API Integration2h
- Build a multi-page Streamlit dashboard for your SLM + agent
Production Deployment — FastAPI Backend, Docker Containerization, Hugging Face Spaces2h
- Containerize and deploy AI app with a REST API
Responsible AI — Hallucinations, Bias, Safety Red-teaming, Prompt Injection Defense4h
- Audit your own model for bias and safety issues
Capstone Project — Final Build, Polish & Demo Preparation8h
- End-to-end integration: SLM + Agent + Dashboard + Deployment

Mr. ABC

Professor

AI CREATOR BOOTCAMP

Course Overview

Highlights

Learning Outcomes

Course Curriculum

Meet your instructor

Mr. ABC

Ready to start AI CREATOR BOOTCAMP ?

AI CREATOR BOOTCAMP

Course Overview

Highlights

Learning Outcomes

Course Curriculum

Meet your instructor

Mr. ABC

Ready to start AI CREATOR BOOTCAMP ?