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5 courses · Lucknow & Live Online

AI, Generative AI & Agentic AI Courses

From ChatGPT productivity for non-coders to building production AI agents with LangGraph, RAG and MLOps — the fastest-growing skill set in Indian IT hiring.

Quick answer
BPST Academy offers five AI courses in Lucknow and live online: Agentic AI Engineering, Generative AI for Everyone (prompt engineering, no coding), MLOps/LLMOps, an AI specialization and a Machine Learning specialization. Courses run 4 weeks to 5 months and every learner builds a working AI project.
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Course 01 · Build AI agents that reason, use tools and get work done

Agentic AI Engineering

Go beyond chatbots. Learn to build production AI agents with LLM APIs, RAG, LangGraph and CrewAI, connect them to real tools through function calling and MCP, and ship them with evaluation, guardrails and tracing.

Best for: Developers, B.Tech/MCA final-year students and working professionals with basic Python.

Pre-book ₹49 Full syllabus
Duration
3 – 5 Months
Level
Intermediate
Mode
Classroom (Lucknow) / Live online
Pre-book
₹49 till Diwali

Syllabus — module by module

Module 01
LLM Foundations & Prompting
  • How LLMs work: tokens, context, temperature
  • Prompt patterns & structured output
  • OpenAI, Claude & Gemini APIs
  • Cost and latency control
Module 02
RAG & Vector Databases
  • Embeddings & chunking strategies
  • FAISS, Chroma & pgvector
  • Hybrid search & re-ranking
  • Citations and grounding
Module 03
Tool Calling & MCP
  • Function / tool calling
  • Model Context Protocol (MCP) servers
  • Calling REST APIs & databases
  • Safe action design
Module 04
Agent Frameworks
  • LangGraph state machines
  • CrewAI & AutoGen multi-agent teams
  • Planning, memory & reflection
  • Human-in-the-loop approvals
Module 05
Evaluation & Guardrails
  • LLM evals & test sets
  • Hallucination & safety checks
  • Tracing with LangSmith
  • Prompt-injection defence
Module 06
Deploying Agents
  • FastAPI backends & streaming
  • Docker & cloud deployment
  • Monitoring & cost dashboards
  • Capstone demo day

Projects you build

  • Customer-support agent with RAG over company docs
  • Multi-agent research & report writer
  • Email/CRM automation agent with human approval

You will be able to

  • Design and ship an AI agent end-to-end
  • Build reliable RAG pipelines with citations
  • Evaluate and monitor LLM apps in production
  • Explain agent architecture confidently in interviews

Tools & tech

PythonOpenAI / Claude / Gemini APIsLangChainLangGraphCrewAIMCPFAISS / ChromaFastAPIDockerLangSmith

Maps to Microsoft AI-102 and AWS Certified AI Practitioner

Course 02 · Use ChatGPT, Claude, Gemini & Copilot to work 10× smarter — no coding

Generative AI for Everyone (Prompt Engineering)

A practical, no-code course for students, office professionals, teachers and business owners. Master prompt engineering, AI for Excel, PowerPoint and documents, image and video generation, and simple no-code automations.

Best for: Students of any stream, working professionals, managers, teachers and business owners.

Pre-book ₹49 Full syllabus
Duration
4 – 8 Weeks
Level
Beginner
Mode
Classroom (Lucknow) / Live online
Pre-book
₹49 till Diwali

Syllabus — module by module

Module 01
How Generative AI Works
  • LLMs in plain language
  • What AI can and cannot do
  • Choosing ChatGPT, Claude, Gemini or Copilot
  • Privacy & responsible use
Module 02
Prompt Engineering
  • Role, context, task & format
  • Few-shot examples
  • Chain-of-thought & step prompts
  • Reusable prompt templates
Module 03
AI for Office Work
  • Excel formulas & analysis with AI
  • PowerPoint decks in minutes
  • Emails, reports & summaries
  • Meeting notes & action items
Module 04
Creative AI
  • Image generation & editing
  • AI video & voice tools
  • Social media content
  • Brand consistency
Module 05
No-code Automation
  • Custom GPTs & projects
  • n8n / Zapier basics
  • Auto-reply & lead workflows
  • Research assistants
Module 06
AI Career Toolkit
  • Resume & LinkedIn with AI
  • Interview prep with AI
  • Portfolio of AI work
  • AI ethics & policy

Projects you build

  • Personal prompt library for your job
  • AI-generated sales deck & report
  • No-code lead-reply automation

You will be able to

  • Write prompts that get reliable results
  • Automate repetitive office tasks
  • Create content and presentations with AI
  • Use AI safely at work

Tools & tech

ChatGPTClaudeGeminiMicrosoft CopilotCanva AIn8nZapier

Maps to Google AI Essentials and Microsoft AI-900 fundamentals

Course 03 · Take ML and LLM models from notebook to production

MLOps & LLMOps

Learn the engineering that keeps AI running: experiment tracking, data versioning, CI/CD for models, model serving, monitoring and drift detection, and LLM evaluation and cost control on AWS and Azure.

Best for: Data scientists, ML engineers, DevOps engineers and developers moving into AI platforms.

Pre-book ₹49 Full syllabus
Duration
3 – 6 Months
Level
Advanced
Mode
Classroom (Lucknow) / Live online
Pre-book
₹49 till Diwali

Syllabus — module by module

Module 01
ML Lifecycle
  • Problem framing to deployment
  • Reproducible projects
  • Feature stores intro
  • Model registry concepts
Module 02
Tracking & Versioning
  • MLflow experiments
  • DVC data versioning
  • Model registry
  • Artifact storage
Module 03
Containers & Pipelines
  • Docker for ML
  • Kubernetes basics
  • Kubeflow / Airflow pipelines
  • GitHub Actions CI/CD
Module 04
Model Serving
  • FastAPI & BentoML
  • vLLM for LLMs
  • Batch vs real-time
  • Autoscaling
Module 05
Monitoring
  • Data & concept drift
  • Prometheus & Grafana
  • LLM evals in production
  • Alerting
Module 06
Cloud ML Platforms
  • AWS SageMaker
  • Azure ML
  • Cost optimisation
  • Capstone deployment

Projects you build

  • End-to-end ML pipeline with CI/CD
  • LLM serving with vLLM + monitoring
  • Drift detection dashboard

You will be able to

  • Productionise ML and LLM models
  • Automate training & deployment pipelines
  • Monitor model quality and cost

Tools & tech

PythonMLflowDVCDockerKubernetesFastAPIvLLMPrometheusGrafanaSageMakerAzure ML

Maps to AWS ML Engineer Associate and Azure DP-100

Course 04 · Specialization program

Artificial Intelligence (AI + Generative AI)

Understand how intelligent systems work and build real AI products — search, reasoning, NLP, computer vision and modern LLM-powered agents.

Best for: Students and developers curious about building AI products.

Pre-book ₹49 Full syllabus
Duration
4 Months
Level
Python basics required
Mode
Classroom (Lucknow) / Live online
Pre-book
₹49 till Diwali

Syllabus — module by module

Module 01
AI Foundations
  • What is AI · types of AI
  • Intelligent agents
  • Search: BFS, DFS, A*
  • Knowledge representation
Module 02
Python for AI
  • NumPy & Pandas
  • Data handling
  • APIs & JSON
  • Jupyter workflow
Module 03
NLP
  • Text preprocessing
  • Sentiment analysis
  • Embeddings
  • Transformers overview
Module 04
Computer Vision
  • Images as data
  • OpenCV basics
  • Face / object detection
  • Pre-trained models
Module 05
Generative AI
  • LLM APIs (OpenAI, Gemini, Claude)
  • Prompt engineering
  • RAG with vector DBs
  • LangChain
Module 06
AI Agents & Ethics
  • Tool-using agents
  • Multi-step workflows
  • Responsible AI & bias
  • Deploying AI apps

Projects you build

  • Document Q&A chatbot (RAG)
  • Face-detection attendance app
  • AI study-assistant agent

You will be able to

  • Explain core AI concepts clearly
  • Build NLP and vision mini-apps
  • Create a RAG chatbot over documents
  • Build a simple AI agent

Tools & tech

PythonOpenCVHugging FaceOpenAI APILangChainChromaDBStreamlit

BPST AI Certificate

Course 05 · Specialization program

Machine Learning

A rigorous, hands-on ML course — maths intuition, classical algorithms, model evaluation, deep learning basics and deployment.

Best for: Engineering / CS / maths students targeting ML engineer roles.

Pre-book ₹49 Full syllabus
Duration
4 Months
Level
Python basics required
Mode
Classroom (Lucknow) / Live online
Pre-book
₹49 till Diwali

Syllabus — module by module

Module 01
Maths & Statistics
  • Vectors & matrices
  • Probability & distributions
  • Descriptive stats
  • Gradient descent
Module 02
Data Preparation
  • EDA with Pandas
  • Missing values & outliers
  • Encoding & scaling
  • Feature engineering
Module 03
Regression & Classification
  • Linear, polynomial, logistic
  • KNN, Naive Bayes, SVM
  • Decision trees
  • Random forest & XGBoost
Module 04
Unsupervised Learning
  • K-means
  • Hierarchical clustering
  • PCA
  • Recommendation systems
Module 05
Model Evaluation
  • Train/test, cross-validation
  • Accuracy, precision, recall, F1
  • ROC-AUC
  • Hyper-parameter tuning
Module 06
Deep Learning & MLOps
  • Neural networks
  • Keras / TensorFlow
  • Model serving with FastAPI
  • Deploy on cloud

Projects you build

  • Loan-approval predictor
  • Movie recommender
  • Handwritten digit recognizer

You will be able to

  • Choose, train and tune the right algorithm
  • Evaluate models with correct metrics
  • Build a neural network
  • Deploy an ML model as an API

Tools & tech

PythonScikit-learnXGBoostTensorFlowKerasPandasFastAPI

BPST ML Certificate

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Generative AI & Agentic AI

Create | Automate | Augment | Build the Next AI Era

Learn the cutting-edge generation of AI with Large Language Models (LLMs), Retrieval Augmented Generation (RAG), autonomous AI agents, and intelligent workflows.

Key Technologies:
Prompt EngineeringLLMs (OpenAI, Gemini, Claude)RAG ArchitecturesVector DBs (Chroma, Pinecone)LangChain & LlamaIndex+3 more
45 Days · 3 Months · 6 Months Beginner friendly
View Syllabus & Roadmap Pre-book for ₹49 Enquire for this course

AI & Generative AI — Frequently Asked Questions

If you do not code, start with Generative AI for Everyone (4–8 weeks). If you know basic Python, choose the AI specialization or Agentic AI Engineering to build RAG apps and AI agents.

Yes. Gartner expects around 40% of enterprise applications to include task-specific AI agents by the end of 2026, and NASSCOM reports a large gap between AI talent demand and supply in India.

Every AI course ends with a capstone: a RAG chatbot, a multi-agent workflow or a deployed ML model, pushed to GitHub with a live demo.

Last updated 2026-09-25

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