🎓 AI Vidya 3-Month Basic AI & ML Foundation Program

From Zero to Data-Driven Beginner

Join the Foundation Program

🧭 Program Overview

AI Vidya 3-Month Basic AI & ML Foundation Program

Duration	3 Months (12 Weeks)
Level	Beginner
Mode	Mentor-led + Self-paced Learning
Outcome	Foundational Certificate + Mini Project Portfolio

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🔹 Phase 1: Python & Data Fundamentals (Month 1)

Goal: Build programming logic and comfort with data handling.

Week 1 – Python for Data Science

• Introduction to Python & Jupyter Notebooks

• Data types, loops, functions, and libraries

• Hands-on with NumPy and Pandas

• Mini Project: Simple Data Profiler (summarize any CSV file)

Week 2 – Working with Data

• Reading/writing CSV, Excel, JSON files

• Handling missing values and duplicates

• Data manipulation using Pandas

• Exercise: Analyze a small e-commerce dataset

Week 3 – Data Visualization

• Matplotlib, Seaborn, and Plotly basics

• Creating bar, line, scatter, and heatmap charts

• Telling stories with data

• Mini Project: IPL or COVID-19 Data Visualization Dashboard

Week 4 – Statistics & Probability Basics

• Descriptive statistics (mean, median, variance)

• Probability, distributions, correlation, covariance

• Basic linear algebra concepts for ML

• Assignment: Analyze a dataset using statistical measures

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🔹 Phase 1: Python & Data Fundamentals (Month 1)

Goal: Build programming logic and comfort with data handling.

Week 1 – Python for Data Science

• Introduction to Python & Jupyter Notebooks

• Data types, loops, functions, and libraries

• Hands-on with NumPy and Pandas

• Mini Project: Simple Data Profiler (summarize any CSV file)

Week 2 – Working with Data

• Reading/writing CSV, Excel, JSON files

• Handling missing values and duplicates

• Data manipulation using Pandas

• Exercise: Analyze a small e-commerce dataset

Week 3 – Data Visualization

• Matplotlib, Seaborn, and Plotly basics

• Creating bar, line, scatter, and heatmap charts

• Telling stories with data

• Mini Project: IPL or COVID-19 Data Visualization Dashboard

Week 4 – Statistics & Probability Basics

• Descriptive statistics (mean, median, variance)

• Probability, distributions, correlation, covariance

• Basic linear algebra concepts for ML

• Assignment: Analyze a dataset using statistical measures

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🔹 Phase 3: Practical AI Application + Career Skills (Month 3)

Goal: Build small AI apps, learn deployment basics, and prepare for internships.

Week 9 – Model Improvement

• Cross-validation, feature selection, scaling

• Model saving/loading with Pickle/Joblib

• Assignment: Optimize your best model

Week 10 – Model Deployment Basics

• Introduction to Flask and Streamlit

• Create a simple ML Web App

• Mini Project: Deploy your classifier on Streamlit

Week 11 – Real-World Use Cases

• How AI is used in finance, marketing, healthcare

• Overview of NLP and Deep Learning concepts (preview for next level)

• Group Project: Business Case Presentation

Week 12 – Capstone & Career Readiness

• Capstone Project (choose one):

  • Predictive Analytics on Real Dataset

  • EDA on Company or Market Data

  • Classification Model with Dashboard

• Resume & LinkedIn building session

• AI Vidya Foundation Certificate

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🧩 Program Deliverables

• 6+ Hands-on Projects

• 1 Capstone Project

• Career Mentorship Session

• GitHub Portfolio Guidance

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💼 Career Outcomes

After this program, learners can apply for:

• Data Science Internships

• AI/ML Student Research Projects

• Entry-level Data Analyst roles

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💬 Mentorship & Support

• Weekly mentor calls

• Discord learning community

• Peer review and feedback on assignments

Start from zero and build your first AI projects — no coding experience needed.

Join the Foundation Program