Is your Python ready?
You should write functions and classes, install packages, work at the command line and call a REST API.
80-hour live-online cohort · For Python developers
AI Engineering Course Bangalore
Build RAG applications, controlled agents, MCP integrations and deployable AI services through 40 live hours and about 40 hours of guided project work.
- Programme
- 80 hours across eight weeks
- Live classes
- 40 hours on Zoom
- Guided work
- About 40 project hours
- Portfolio
- Five GitHub projects with demos
Direct answer
What is AI Engineering Course Bangalore?
AI Engineering Course Bangalore is Technovids’ live-online, eight-week programme for developers who already write Python. It combines 40 hours of instructor-led Zoom classes with about 40 hours of guided work across five GitHub portfolio projects. The curriculum covers model APIs, RAG and evaluation, LangGraph-based controlled agents, MCP integrations, FastAPI, Docker, deployment and operational review. Technovids is headquartered in HSR Layout, Bengaluru; the public cohort is online and does not include classroom attendance.
Updated
Who this page is for
Relevant audiences
- Backend, full-stack and platform developers comfortable with Python
- Data and ML professionals moving into LLM application engineering
- DevOps engineers supporting AI services and deployment
- Technical career switchers who meet the programming prerequisites
Useful when
- You can follow tutorials but cannot yet design an end-to-end AI application
- You need a structured route across RAG, agents, MCP and deployment
- You want projects you can demonstrate and explain rather than copy
- You need instructor review and a weekly learning rhythm
Scope boundary: This is not a beginner Python course, a job guarantee or a promise that classroom projects are production-ready. Participants arrange a suitable laptop and their own model API usage if required.
Decision guide
Check readiness before choosing the 80-hour route
The programme moves quickly because it builds on programming fundamentals rather than teaching Python from zero.
Can you protect build time?
Plan for roughly five live hours and five guided project hours a week across eight weeks.
Can you use external services?
Projects may require model APIs and hosting. Learners use eligible free tiers where suitable or their own paid account and usage.
What counts as completion?
Meet the stated attendance and submission requirements and complete the five project checkpoints.
Five portfolio builds
Build an evidence trail across the AI application stack
Each build has an acceptance check and a hosted demonstration path; hosting depends on platform eligibility and the learner’s own account.
Structured model API service
Create a small service with validated inputs, structured outputs, retries and error handling.
- Practise
- Test invalid inputs, provider errors, output schemas, cost and latency.
- Control
- A working endpoint is not production-ready without security and operational review.
Measured RAG assistant
Ingest documents, retrieve evidence and answer with citations.
- Practise
- Build a query–evidence set and improve one measured retrieval or answer failure.
- Control
- RAG reduces neither hallucination risk nor the need for permissions and review.
Controlled LangGraph agent
Use tools, state, stopping rules and a human approval checkpoint.
- Practise
- Trace successful, ambiguous, denied and tool-failure runs.
- Control
- The agent receives no authority beyond the application’s constrained tools.
MCP integration
Connect a compatible client and server with scoped tools or resources.
- Practise
- Inspect capabilities, authentication, returned data and failure behaviour.
- Control
- Connecting an MCP server changes the security boundary and requires trust review.
Integrated capstone
Combine API, retrieval or agents with deployment, evaluation and operations evidence.
- Practise
- Document architecture, test results, threats, cost assumptions and remaining gaps.
- Control
- A hosted demo is portfolio evidence, not a service-level or production claim.
Technical walkthrough
Explain decisions, failures and trade-offs from the code and evidence.
- Practise
- Demonstrate the system and answer architecture, evaluation and control questions.
- Control
- The certificate does not substitute for the ability to explain the work.
Options
Choose the complete course or a narrower route
Use the broader programme when the goal is an end-to-end transition; use focused pages when one missing capability is clear.
This page
AI Engineering Course
The full 80-hour live and guided public-cohort route.
Best for: Individual Python developers seeking structured portfolio work
- RAG, agents and MCP
- Five projects
- Live online over eight weeks
AI Programming with Python
Strengthen the Python, API and data-handling foundation first.
Best for: Learners not yet comfortable with the prerequisites
- Python application skills
- APIs and data
- Practical preparation
Focused technical training
Go directly to RAG, LangChain, MCP or agentic AI when foundations are already strong.
Best for: Developers solving one architecture or framework gap
- Narrow scope
- Current framework practice
- Course availability confirmed separately
Production AI Engineering for teams
Use the private corporate programme when an employer is training its own engineering group.
Best for: Company developer teams and technical leaders
- Private cohort
- Client-relevant scope
- Five 8-hour or ten 4-hour days
Public AI Engineering course versus private team programme
The technical domain overlaps, but audience, schedule and evidence model differ.
| Decision point | Public 80-hour course | Private corporate programme |
|---|---|---|
| Audience | Individual Python developers | One organisation’s engineering team |
| Format | 40 live hours + about 40 project hours | 40 hours as five full or ten half days |
| Context | Portfolio-oriented project briefs | Client-relevant examples and team constraints |
| Commercials | Confirmed with the scheduled cohort | Confirmed in a corporate proposal |
Practical value
What a completing learner should be able to demonstrate
The result is a set of explainable projects and engineering evidence, not a placement or production-readiness claim.
Architecture decisions
Explain component boundaries, alternatives, data flow and important trade-offs.
Working project demonstrations
Run the five builds and show how inputs, outputs, errors and controls behave.
Evaluation evidence
Use representative tests and traces to discuss quality, failure, latency and cost.
Production-gap awareness
Identify security, scale, observability, data and support work beyond the classroom build.
Method
From course enquiry to applied practice
The next confirmed cohort information is shared before enrolment, and the learning path keeps practice and review visible.
- 01
Check course fit
Share your background, current tools and goal. Chandan discusses fit first; a subject-matter expert follows up when technical depth is needed.
- 02
Review the confirmed offer
Receive the current dates, live schedule, fee, prerequisites, inclusions and cancellation or transfer terms before deciding.
- 03
Prepare accounts and environment
Complete the stated setup using your own suitable device and any accounts or paid API access required for the selected course.
- 04
Attend, practise and review
Join live Zoom classes, complete exercises or projects, use LMS resources and apply instructor feedback.
- 05
Complete the learning evidence
Submit the agreed work and receive a Technovids completion certificate with a unique website-verifiable ID when the stated requirements are met.
Included in the confirmed public cohort
The course combines live teaching, guided building and a consistent online learning environment.
Participants provide their own laptop. Any paid model API usage or learner-owned AWS/Azure account charges are paid directly by the learner; eligible free hosting tiers may be used where suitable.
40 hours of live classes
Weekend or weekday late-evening Zoom sessions, with the exact timetable confirmed per cohort.
About 40 hours of guided project work
Five project briefs, checkpoints, lab instructions and trainer review.
Technovids LMS and recordings
Notes, assignments, lab instructions, cohort group and recordings uploaded within 24 hours with three months of access.
Verifiable completion certificate
A Technovids certificate with a unique website-verifiable ID when course requirements are met.
Safe application
Safe use is taught inside the workflow
Participants practise AI assistance with organisational boundaries and human accountability visible at every material step.
Use approved tools and data
Accounts, confidential information, personal data and intellectual property follow the organisation’s existing policies and approved environment.
Verify consequential output
Facts, calculations, sources, tone, completeness and decision impact are checked against the original material and task.
Retain a human owner
AI can assist drafting or analysis; an accountable person still reviews the work and owns the action or decision.
Measure one bounded use case
Teams compare quality, effort, adoption and risk for a defined workflow rather than claiming generic productivity gains.
Primary sources
Current technical references
Framework and protocol versions are checked before each cohort; official documentation remains the source of truth for changing APIs.
Training in action
See Technovids training in practice
Real instructor-led sessions from the Technovids delivery archive. The photographs show delivery context; they do not imply a result for a future cohort.
Photo 1 of 10: Hands-on session 
Photo 2 of 10: Group photo 
Photo 3 of 10: Hands-on session 
Photo 4 of 10: Group photo 
Photo 5 of 10: Classroom session 
Photo 6 of 10: Group photo 
Photo 7 of 10: Computer-lab session 
Photo 8 of 10: Group photo 
Photo 9 of 10: Classroom session 
Photo 10 of 10: Group photo
Trainers
Meet the Technovids trainer panel
Technovids assigns a suitable trainer after the audience, subject depth and delivery needs are confirmed.
Pankaj Rana
Co-founder & Lead Instructor, Technovids Consulting
Pankaj is a co-founder and the lead instructor at Technovids Consulting. His programme work spans practical AI adoption, AI engineering, evaluation, responsible production AI, data analytics and corporate learning design, with an emphasis on hands-on exercises connected to workplace tasks.
Expertise:
- Practical AI adoption
- Prompting and evaluation
- Responsible AI
- Corporate learning design
Junaid Khateeb
AI & Machine Learning Trainer, Strategist and Consultant
Junaid is an AI and machine-learning trainer, strategist and consultant with more than 22 years of training experience. His work combines enterprise AI education, business-centred adoption, responsible AI practices and applied solution design, helping professional audiences connect AI concepts to real organisational needs.
M.E. in Computer Engineering, specialising in Artificial Intelligence · author of programming books on Python, Java and C++
Expertise:
- Enterprise AI and ML training
- AI strategy and adoption
- Responsible AI
- Applied AI solution design
Pradeep Varadarajan
Technical Trainer & Curriculum Architect
Pradeep is a technical trainer and curriculum architect with more than 20 years of experience across enterprise technology, cloud infrastructure and advanced AI systems. He designs practitioner-focused programmes, labs and assessments covering AI, LLM systems, Python and machine learning, translating complex technical subjects into structured learning experiences.
Bachelor of Engineering in Electrical Engineering · instructor-led, virtual and blended delivery
Expertise:
- AI and LLM systems
- Curriculum architecture
- Python and machine learning
- Hands-on lab design
The proposal names or confirms the trainer assignment for the engagement; every trainer shown here does not teach every programme.
Updated
Client & participant proof
Technical learner perspectives and delivery evidence
Approved learner feedback and training photographs help you inspect the wider delivery experience. They are not employment, certification or project-result guarantees.
Organisations we have delivered training for
Practical training programmes delivered for learners, professionals and teams across AI, data, cloud, productivity and professional skills.
Participant voice
Participant experiences across workplace roles
What professionals found useful, practical and relevant to their day-to-day work.
- Rahul DesaiSenior Software Engineer
I had been trying to transition from traditional backend development to Generative AI, but self-learning was getting overwhelming. The AI Engineering course at Technovids gave me the exact structured roadmap I needed. The modules on LLM architectures and practical prompt engineering are brilliant. It’s not just theory; you actually build functional AI applications. Highly recommend this for working professionals looking to upgrade their tech stack.
- Priya NatarajanData Scientist
Finding a course that goes deep into Retrieval-Augmented Generation (RAG) is surprisingly hard. Most just scratch the surface. Technovids delivered an incredibly detailed deep dive into RAG pipelines, LangChain, and LlamaIndex. The hands-on projects helped me understand how to manage vector databases and chunking strategies effectively. It’s easily the most practical Generative AI training I’ve taken.
- Amit SharmaTechnical Lead
If you want to understand agentic AI, this is the course to take. The instructor did a fantastic job breaking down complex topics like LangGraph and cyclical agents, which are rarely covered well in other bootcamps. Learning how to orchestrate multiple AI agents to solve complex workflows has completely changed how I approach architecture at my current job. Worth every penny.
- Sneha ReddyFull Stack Developer
What I loved most about the Technovids GenAI program is how up-to-date the curriculum is. Instead of outdated practices, we learned to integrate the Model Context Protocol (MCP) and practically apply tools like Claude and Cursor for AI-assisted coding. It felt like I was learning the exact skills that top tech companies are hiring for right now. The pace is perfect, and the support is great.
- Neha GuptaBackend Developer
I was initially intimidated by the math and complexity behind AI, but the trainers at Technovids explain things in such an accessible way. They break down everything from basic prompt engineering to complex integrations without losing you in the jargon. The session recordings and project materials are top-notch. If you are serious about becoming an AI Engineer, Technovids provides the perfect launchpad.
- Anjali VermaSystems Analyst
I didn't want a purely academic course; I wanted to code. Technovids pushes you to actually build things. The curriculum is heavily focused on real-world use cases, ensuring you know how to build robust, scalable applications using LangChain and advanced AI models. It’s intensive, fast-paced, and exactly what the current job market demands.
Frequently asked questions
Published answers define the page scope. A written proposal records engagement-specific terms.
How long is the AI Engineering Course?
It is an 80-hour programme across eight weeks: 40 hours of live instructor-led Zoom classes plus about 40 hours of guided project work. The confirmed cohort timetable states the exact days and times.
What Python level is required?
You should be comfortable with functions, classes, lists and dictionaries, installing packages, basic command-line work and calling a REST API from Python. If not, start with AI Programming with Python.
Are all five projects deployed live?
Each project has a hosted demonstration path. Learners can use a compatible eligible free tier such as Vercel or Cloudflare where appropriate, or their own AWS or Azure free or paid account. Availability and charges depend on the platform and learner account.
Who pays model API and hosting costs?
Learners pay providers directly for their own usage when paid access is required. Suitable free tiers can be used where available and eligible; Technovids does not promise that every project remains free to host or run.
Are AI Engineering classes held at the HSR Layout office?
No. HSR Layout is the Technovids head office, not a public classroom. Confirmed public cohorts run live online through Zoom. The Technovids LMS includes notes, assignments, lab instructions, a cohort discussion group and a completion certificate when requirements are met. Class recordings are uploaded within 24 hours and remain available for three months.
Does the certificate guarantee a job?
No. The Technovids completion certificate records programme completion and can be verified using its unique ID on the website. Employment depends on demonstrated skill, experience, interviews and employer decisions.
Technovids Consulting
Bengaluru head office. India-wide live delivery.
2nd Floor, Chandrodaya Complex, 19/19, 24th Main Rd, near Hanuman Temple, Agara Village, 1st Sector, HSR Layout, Bengaluru, Karnataka 560102.
Please contact us before visiting the head office. The HSR Layout address is a head office, not a walk-in public classroom.