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Learn from Industry Experts
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Weekdays / Weekend batches available
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Get 100% placement assistance
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Special batches for job seekers

Students

10000+ Students Trained

Placement

100% Placement Assistance

Start Date

03-Nov-2025

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Program Details

Master end-to-end AI engineering — from building and training ML models to deploying them as scalable FastAPI endpoints. Learn to secure, optimize, and deploy AI services for real-world use cases. Key Highlights: Build & deploy ML/DL models using FastAPI Learn Python, API design, and MLOps fundamentals Hands-on projects & industry-level capstone Cloud deployment (Azure / AWS) Job-ready skills for AI Engineer roles Career Outcomes: AI Engineer • ML Engineer • API Developer • Data Engineer

Key Features of the Course
  • Learn from Industry Experts
  • Weekdays batches available for working professionals and college going students
  • Weekend batches available for working professional
  • Get 100% placement assistance
  • Get classes as per your availability
  • Special batches for job seekers
Syllabus

Objective

Build foundational understanding of AI engineering workflows and API architecture.

Topics

  • What is AI Engineering? How it differs from Data Science & ML Engineering
  • Overview of AI product lifecycle: Data ? Model ? Endpoint ? Deployment ? Monitoring
  • What are REST APIs and why AI Engineers must know them
  • Understanding endpoints, HTTP methods (GET, POST, PUT, DELETE)
  • JSON request/response formats and status codes
  • Introduction to FastAPI and its advantages over Flask/Django
  • Environment setup (Python, FastAPI, Uvicorn, VS Code/Postman)

Lab

Create a “Hello AI Engineer” FastAPI project and run your first endpoint.

Assignment

Build an endpoint /info that returns a JSON with your name, skill interests, and learning goals.

Objective

Strengthen Python skills needed for scalable AI endpoint development.

Topics

  • Modular programming and Python package structure
  • Type hints & Pydantic models
  • Async & Await fundamentals
  • Exception handling and custom error messages
  • JSON parsing, dependency injection in FastAPI
  • API routing and request/response schema design
  • Handling query parameters, path parameters, and request bodies

Lab

Build an endpoint /predict_age_group that accepts name & age, validates inputs, and returns an age group.

Assignment

Design a multi-endpoint FastAPI application with clean structure using routers.

Objective

Learn to build, train, and serialize ML models for API serving.

Topics

  • AI/ML landscape overview: supervised vs unsupervised
  • Model pipeline using scikit-learn (data preprocessing ? training ? evaluation)
  • Model persistence using joblib/pickle
  • Reproducibility and versioning (saving preprocessing steps + model)
  • Loading models back in Python scripts

Lab

Train a Decision Tree Classifier to predict student performance and save it as a .pkl file.

Assignment

Build and save a regression model (house price prediction) for use in APIs.

Objective

Expose ML models via REST endpoints.

Topics

  • Integrating pre-trained ML models into FastAPI apps
  • Defining request/response Pydantic models
  • Model loading on startup (FastAPI event handlers)
  • Inference endpoint design
  • Input validation, error handling, and logging
  • Return predictions and probabilities

Lab

Expose the student performance model as /predict_performance endpoint.

Assignment

Convert your Week 3 regression model into an API endpoint with appropriate input schema.

Objective

Deploy AI models built using TensorFlow/PyTorch or Hugging Face Transformers.

Topics

  • Overview of DL/NLP/CV models
  • Serving a pre-trained model (e.g., sentiment analysis or image classifier)
  • Using Hugging Face pipelines with FastAPI
  • Handling file uploads (image/text input)
  • Managing large models efficiently (lazy loading, caching)

Lab

Deploy a text sentiment analysis model as an API endpoint.

Assignment

Choose a model (e.g., image classifier, summarizer, or chatbot) and deploy it as /analyze endpoint.

Objective

Build high-performance, production-ready endpoints.

Topics

  • Concurrency in FastAPI: async endpoints and background tasks
  • Handling streaming responses
  • Using Redis or Celery for background jobs
  • Pagination, filtering, and batching
  • Logging, tracing, and metrics
  • Rate limiting & API versioning

Lab

Build a batch inference endpoint that accepts multiple inputs and processes them asynchronously.

Assignment

Create an endpoint that logs each prediction request into a log file or database.

Objective

Secure AI endpoints for enterprise-grade applications.

Topics

  • API authentication methods (API key, OAuth2, JWT)
  • Handling CORS and HTTPS
  • Role-based access control (RBAC)
  • Input sanitization and request throttling
  • Environment variables & secrets management
  • Introduction to scaling APIs using Nginx, Gunicorn, or Uvicorn workers

Lab

Secure your /predict endpoint using API key-based authentication.

Assignment

Implement JWT authentication for your model endpoint.

Objective

Learn to deploy AI endpoints and manage ML workflows.

Topics

  • Introduction to Docker for containerization
  • Dockerizing FastAPI apps with models
  • Continuous Integration / Continuous Deployment (CI/CD) overview
  • Deployment options:
    • Azure App Service
    • AWS Lambda + API Gateway
    • Google Cloud Run
  • MLOps concepts: model versioning, monitoring, retraining pipelines
  • Logging with Prometheus/Grafana

Lab

Containerize your FastAPI ML app using Docker and deploy it locally.

Assignment

Deploy the container to Azure or Render (free hosting) and share live endpoint URL.

Objective

Integrate AI APIs into real-world systems.

Topics

  • Integrating AI endpoints with frontend (React, Streamlit, or Flask UI)
  • Real-time chatbot integration example (FastAPI + OpenAI API)
  • Recommendation engine API example
  • AI microservices architecture overview
  • Logging user analytics & feedback for continuous improvement
  • Responsible & ethical AI deployment practices

Lab

Integrate your API with a small Streamlit app for interactive inference.

Assignment

Build an AI microservice (e.g., chatbot or recommender) and integrate it with a web interface.

Objective

Demonstrate end-to-end AI Engineering skills.

Capstone Project

Each student selects one project:

  • Text Summarization API
  • Image Captioning API
  • Resume Screening API
  • Sentiment Analysis Chat API
  • Product Recommendation API

Deliverables

  • AI model (.pkl / .pt / .h5 / Hugging Face)
  • FastAPI service with security
  • Dockerized deployment
  • API documentation (Swagger + ReadMe)
  • Short demo video

Career Prep

  • Resume writing for AI Engineers
  • GitHub portfolio setup
  • Interview prep (FastAPI, Python, ML, deployment questions)
  • Freelancing and project monetization opportunities
Mentors

We handpick subject-matter experts for video lectures and live sessions.

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Shivam Bhatiya
Data Analyst
8+ Years of Experience

Shivam Bhatiya is a Data Scientist. He is certified in AWS, Azure, and Artificial Intelligence. He has trained in many IITs for M.Tech Students.

5
20000 students
...
Course Details
  • Course: AI Engineer Bootcamp: Building Scalable AI Endpoints with Python & FastAPI
  • Level: Advanced for beginners
  • Total Hour: 100
  • Core Audience: Job seekers
  • Modules Covered: 10
  • Last Updated: 22-Oct-2025

FEE:

Online Virtual Class Room

Enroll in any above batch and attend live class at scheduled time

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Upcoming Batches


03-Nov-2025
8:00 AM IST
Weekdays Batch (1 Hour Mon - Fri)
 Apply ₹0 ₹0 (10% OFF)
Offer Ends in 7 d: 15h : : 27s

Learning Methodology

Our Learning Methdology is different from others. We focus on every aspect from start to end.

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Step 1

Enroll yourself by paying registration fee

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Step 2

Learn into live classes with your dedicated mentors

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Step 3

Solve quizzes & practice Sets

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Step 4

Resume Building & Interview Preparation

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Step 5

Get Placed

Industry Recognized Certification

Wifi Learning is a authorized certiport training center also we are Microsoft testing partner. You will get industry recognized certificates.

Success Stories of our Alumni

Find alumni profiles and know more about their career path, specialisation and more!

Mar-10-2024

Mr. Hussain

Mr Hussain was working in semi technical domain and he wanted to make his career in IT field. He tried many times but due to wrong approach he was not able to get it. Somehow he came to know about our Data Analytics training program. He joined our Data Analytics program. Even he did not finish his training and during training period he got selected in JCI (Johnson & control International) with the package of 16 LPA.

Mar-10-2024

Mr. Amit Bhardwaj

Although he is from non- IT background .After losing his job during Covid pandemic, he has been trying to get it since a long time but unfortunately was not able to get any opportunity. He got to know about Wifi Learning Data Analytics program through internet. He joined this program and fortunately after completion of only 3 modules he cracked two different interviews and he joined E&Y with 11LPA. We as a team Wifi Learning wishing him a great career ahead.

Mar-10-2024

Mr. Mukul

Mr. Mukul was working as a MIS Executive since a long time but his goal was to make his career as a Data Analyst. Due to limited skill sets he was not able to get opportunity. He came to know about Wifi Learning and it’s Data Analytics program through his friend. He joined this program and just after completion of his training, he got placed in Infosys at 20 LPA.

Mar-10-2024

Ms. Bindu

Ms. Bindu was working in Wonderman Thompson at gurgaon location due to some personal reasons she had been trying to relocate to Chennai location but due to market recession and all she could not get any opportunity. She joined our Data Analytics training program in February 2023. Even her training was not completed and she got a very good opportunity in IQ India at her preferred location Chennai with the salary package of 18 LPA.

Hear From
Wifi Learning's Alumini's
Mr Amit Bhardwaj
Mr. Mukesh Kumar

Application Process

There are 3 simple steps in the Application Process which are detailed below:

Step 1
Submit an application

Complete the application and include a brief statement of purpose. The latter informs our admission counseller why you're interested and qualified for the program.

Step 2
Application Review

A panel of admission counseller will review your application and statement of purpose to determine whether you qualify for acceptance

Step 3
Admission

An offer of admission will be made to qualified candidates, you can accept this offer by paying the program fee.

Our Google Reviews

We are delighted to share our recent Google review, which serves as a testament to the exceptional experiences we provide to our valued customers. This glowing review reflects the dedication and hard work of our entire team. Our commitment to delivering top-notch products/services and outstanding customer service is truly paying off, as evidenced by the kind words and five-star rating we received.

Reach Out to Us

  • If you want Training from Industry Experts
  • For corporate training
  • To hire our candidates
  • For empanelment as a trainer

Corporate Training Partners

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Times group is a leading brand in the field of Skills enhancement for corporate in IT and Non IT domain. Wifi learning has been associated with it since last 3 years and served for many corporate.

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Futurense is a company which works on Get Hired, Trained and deployed with fortune 500. We have been continuously working for futurense for various domain specially IT Domain.

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Jain University is a private deemed university in Bengaluru, India. Originating from Sri Bhagawan Mahaveer Jain College, it was conferred the deemed-to-be-university status in 2009. Wifi learning has been associated with it since 2020 and has been serving for B.Tch and MBA candidates.

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SBI Cards & Payment Services Ltd., previously known as SBI Cards & Payment Services Private Limited, is a credit card company and payment provider in India. SBI Card launched in October 1998 by State Bank of India

Our Alumni Work At

Top agencies and brands across the globe have recruited Wifi Learning Alumni.

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