Applied AI & Data Science with Projects
Duration – 3 Days
Objectives
To equip participants with industry-relevant AI &
data analysis skills through project-based
learning, hands-on tools, and deployment
techniques—empowering them for careers in
Data Science, Machine Learning, and AI
application development.
Tools & Platforms
•Google Colab / Jupyter Notebook
•Pandas, Scikit-learn, Keras, TensorFlow
•Streamlit / Huggingface Spaces
Pre-requisites
• Basic Python knowledge (variables, loops, functions)
• Basic math skills (mean, median, probability)
• Familiarity with tools like Google Colab or Jupyter
Notebook
• Interest in data analysis and AI
• Willingness to learn and explore hands-on projects
Take away
• By the end of this 2-day workshop, learners will:
• Perform real-world EDA using Pandas and clean large
datasets
• Build, train, and evaluate ML models for business use
cases
• Gain a practical introduction to NLP and deep learning
concepts
• Deploy an end-to-end AI project using Streamlit or
Huggingface
• Present project outcomes in a peer showcase
Day 2 | Deep Learning, NLP & Deployment
• Neural Networks with Keras
• Introduction to Natural Language Processing (NLP)
• Text Classification or Sentiment Analysis
• Deployment using Stream lit or Hugging face Space
Hands-on Project
Deploy ML/NLP model as a Web App using Stream lit or Hugging face Live Demo + Group
Showcase
