Since 2004 · ISO 9001:2015 · Lucknow & Noida

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Job programs

College trainings

AI LaunchPad

Zero to deployed AI Engineer in 6 months — with 20+ shipped projects, not certificates.

6 months · 24 weeksBeginner-friendlyClassroomHybrid

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Python with Machine LearningData Science · FoundationPython with Data ScienceData Science · Foundation · ~21 hoursGAGen AI & Agentic AIAI Engineering · Intermediate · ~92 hours

Full Stack LaunchPad

From first HTML tag to a deployed full-stack product — a job-focused 4-month build program in your chosen stack.

4 months · 16 weeksBeginner-friendlyClassroomOnline (Live)Hybrid

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Python with DjangoWeb Development · Foundation · ~37 hoursJava with Spring BootProgramming · Foundation · ~39 hoursMERN StackWeb Development · Foundation · 90 DaysPHP with Laravel FrameworkWeb Development · Foundation · 90 Days

Industrial Training

45 / 60 / 90-day industrial training that satisfies your college — and actually teaches you.

45 / 60 / 90 days · year-roundIntermediateClassroomHybrid

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Python with DjangoWeb Development · Foundation · ~37 hoursJava with Spring BootProgramming · Foundation · ~39 hoursPython with Machine LearningData Science · FoundationMERN StackWeb Development · Foundation · 90 Days

Categories

Developer Tools

1 course in this track

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GGGit & GitHubFoundation · ~13 hours

Embedded & IoT

1 course in this track

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Embedded System with Robotics & IoTFoundation

Learn beyond the classroom

Softpro HandshakePractice problems, mock tests and your Hireability Score.GalleryClassrooms, workshops and the students who trained in them.FAQsModes, certificates, batches and how to pick a program.Softpro IndiaThe parent company — products, services and corporate training.

Course · AI Engineering

Gen AI & Agentic AI with Python

Go from calling an LLM API to shipping deployed AI agents — API + async Python, prompt engineering, RAG with vector databases, and deep LangChain + LangGraph agent systems, FastAPI

Intermediate~92 hoursClassroomOnline (Live)

What you'll be able to do

  • Call LLM APIs and write async Python that runs LLM calls concurrently and streams responses
  • Engineer prompts and force validated, structured (Pydantic) outputs from models
  • Build RAG systems with embeddings, ChromaDB / pgvector, chunking, and re-ranking
  • Master LangChain and LangGraph to build stateful, multi-step, multi-agent systems
  • Integrate tools and data into agents with MCP (Model Context Protocol)
  • Serve agents as production APIs with FastAPI, containerize with Docker, and deploy to the cloud
  • Apply production AI engineering: evaluation, observability/tracing, and reliability

Before you start

  • Comfortable with core Python (the Python Power-Up week or equivalent)
  • A laptop that can run Python 3.12, Docker, and a local model via Ollama
  • Free accounts: GitHub, Google AI Studio (Gemini), Groq, Hugging Face, Supabase
  • Willingness to ship deployed projects through the cohort

Tools & technologies

REST APIshttpxAsync PythonPydanticPrompt EngineeringStructured OutputsStreamlitEmbeddingsVector DatabasesChromaDBpgvectorChunking

How you'll learn

AI-nativeYou build with AI tools from the first session — the way working engineers do.
Hands-onMost of every session is you writing code, with mentors reviewing your work.
Project-orientedYou finish with portfolio projects you built — not a certificate for watching videos.
Open by defaultThe course repo is public — everything you'll build is visible before you enroll.

This course's public GitHub repo is shared when the next cohort opens —ask us for a preview and we'll send you the link.

The certificate you'll earn

Sample Softpro certificate of completion (specimen)
  • Issued on program completion, with your name, course and grade.
  • Carries a unique certificate ID and QR code.
  • Anyone can confirm it in seconds on ourcertificate verification page — recruiters included.

A practice-first, project-driven offline cohort that turns Python developers into production-ready AI engineers. You start by filling the engineering gaps the Python week left — API calls, async, and Pydantic — then build LLM apps across multiple providers (Gemini, Groq, Ollama, Hugging Face). You go deep on RAG with embeddings, vector databases (ChromaDB, pgvector/Supabase), chunking, and re-ranking, then master the modern agent stack — LangChain and LangGraph — integrating tools and data via MCP. Finally you serve agents as real products with FastAPI, Docker, and cloud deployment, and learn production AI engineering: evaluation, observability, and reliability. Three deployed mini projects and a deployed capstone. Free-tier-first: no paid OpenAI key required.

Upcoming cohorts

New cohort dates are announced regularly — send an enquiry and we'll reserve you a seat in the next one.