PCAI – Python Course with AI Integration

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About Course

Course Overview

Become an industry-ready Python professional in just 140 training hours through this hands-on, mentor-guided program designed for Software students and aspiring AI developers.
This course integrates the best of Python programming, data science, and applied Artificial Intelligence using today’s most in-demand frameworks — making you ready for real-world software and AI roles.

Whether you aim to become a Python Developer, Data Analyst, ML Engineer, or AI App Developer, this course ensures that you master both the core foundations and modern AI applications that companies like TCS, Zoho, Databricks, Cognizant, and leading AI startups expect from new hires.

All learning progress is tracked through Leadertain.com’s LMS platform, with built-in quizzes, projects, and certificates validated by industry mentors.

Why this course?

  • Learn Python + AI + Data in a single integrated track.

  • Get certified in Python fundamentals and optionally in MongoDB.

  • Build a portfolio of 5+ projects, including an AI chatbot, a deep learning model, and a RESTful API.

  • Designed for job readiness — aligned with current Industry demands.

  • Includes resume and GitHub portfolio guidance for placement support.

Who should enroll

  • B.Tech/B.E. students in CSE, AI, DS, or IT streams.

  • Beginners in Python who aspire to work in AI or backend development.

  • Students preparing for campus placements, hackathons, or internships.

  • Anyone aiming for Python developer, Data Analyst, or ML Engineer roles.

Prerequisites

  • Basic knowledge of programming logic or any introductory computer course.

  • Laptop/desktop with Python 3.x installed (instructions provided in first session).

  • Curious to build and deploy real-world AI projects.

Learning Objectives

By the end of this course, you will be able to:

✅ Write efficient, modular Python code using OOP principles and libraries.
✅ Implement essential Data Structures & Algorithms for coding interviews.
✅ Analyze, clean, and visualize data using NumPy & pandas.
✅ Train, evaluate, and optimize ML models using scikit-learn.
✅ Build and deploy Deep Learning models using PyTorch or TensorFlow.
✅ Apply Generative AI and NLP techniques using Hugging Face and prompt engineering.
✅ Create and consume REST APIs with Flask/FastAPI/Django.
✅ Use SQL & NoSQL (MongoDB) for data persistence and queries.
✅ Collaborate professionally using Git and GitHub.
✅ Present your work as a deployable AI application with a strong technical portfolio.

Course Modules

Module Topics Covered Key Outcome / Project
1. Core Python & Standard Library Variables, control flow, functions, OOP, file I/O, error handling, modules, virtual environments CLI mini-project & coding assignments
2. Data Structures & Algorithms (DSA) Arrays, lists, stacks, queues, trees, searching/sorting, time complexity Solve 20+ DSA problems on LeetCode
3. Python Data Stack (NumPy, pandas) Data frames, indexing, data cleaning, visualization Data analysis project using a real dataset
4. Machine Learning Foundations (scikit-learn) Regression, classification, model evaluation, pipelines Predictive ML model on a business dataset
5. Applied Deep Learning (PyTorch / TensorFlow) Neural networks, CNNs, training loops, evaluation Image classification or sentiment model
6. NLP & Generative AI Tokenization, transformers, LLMs, Hugging Face, prompt engineering Build a Chatbot or Text Summarizer
7. REST APIs & Backend Frameworks Flask / FastAPI / Django basics, endpoints, JSON, and authentication API to serve ML model results
8. Databases (SQL & MongoDB) CRUD operations, schema design, aggregation, Python integration Store and query model results via the database
9. Version Control & Collaboration Git basics, branching, pull requests, GitHub portfolio Team project hosted on GitHub
10. Final Capstone Project & Interview Prep End-to-end AI application with deployment + resume building Deployable portfolio project on Streamlit/Render

Assessment & Certification

  • Weekly quizzes and hands-on labs auto-graded within Tutor LMS.

  • 3 milestone projects and 1 final capstone project were evaluated by mentors.

  • Reputable certification for Python Core / AI Foundations / MongoDB integration.

  • Optional external certifications (e.g., MongoDB University or Python Institute) are supported via course guidance.

Course Duration & Format

  • Duration: 16 weeks (140 hours total)

  • Format: 3 days/week × 3 hours/day (live + LMS integrated practice)

  • Mode: Hybrid – Classroom + LMS online learning modules

  • Progress Tracking: Through LMS dashboard with grades, badges & completion certificates

Tools & Technologies Covered

Python 3.x, NumPy, pandas, scikit-learn, PyTorch/TensorFlow, Hugging Face, Flask, FastAPI, Django, MongoDB, Git/GitHub, Streamlit.

Career Pathways

  • Python Developer

  • Data Analyst / Data Engineer

  • Machine Learning Engineer

  • AI Developer / Prompt Engineer

  • Backend Developer (Flask / Django)

  • Generative AI Solutions Associate

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