Introduction to Data Science and
Artificial Intelligence
Build a solid foundation in data science thinking and gain comprehensive knowledge of the 3 pillars of data (Structured Data, Computer Vision, NLP). This course focuses on problem fundamentals, standard data processing workflows, and practical applications to give you the most hands-on perspective of the field.
Course Overview
Target Audience
Grade 10-11 students
Approach
Foundation & Real skills
Organizers
The Noders Community × PRISEE
Duration
4 sessions (Apr 2026)
What You'll Achieve
Data Thinking
Form correct analytical mindset
Workflow
Standard professional process
Foundation
Ready for advanced levels
Comprehensive
Structured, Vision & NLP
Course Curriculum
4 comprehensive sessions, each 1 hour 30 minutes
Data Science Thinking & Standard Workflows
Overview
- Definition & Analytics comparison
- 3 Pillars: Structured, Vision, NLP
Standard Workflow
- Collection & Pre-processing
- Modeling & Visualization
Case Study
- IELTS score analysis
Data Processing & Visualization
Tool Ecosystem
- SQL for data extraction
- Pandas for processing
- Matplotlib for visualization
Hands-on Practice
- Basic SQL queries
- Data cleaning with Pandas
- Insightful chart creation
Computer Vision & Basic Machine Learning
Image Fundamentals
- Pixel Matrix representation
- Preprocessing: Resize, Grayscale
Algorithms
- KNN principles & classification
- CNN & Deep Learning intro
Practice
- Handwritten digit recognition
Natural Language Processing & Model Evaluation
NLP Fundamentals
- Text cleaning & Tokenization
- BoW, TF-IDF, Word embeddings
Model Evaluation
- Key metrics: Accuracy, F1, etc.
- Context-based metric selection
Course Material
Lecture Notes
Teaching Slides
Practice Notebooks
Lecture_2_Demo.ipynb
SQL, Pandas & Visualization
Hands-on practice with data querying, manipulation, and creating insightful visualizations
Lecture_3_Demo.ipynb
KNN Algorithm & Computer Vision
Build classification models and explore image processing fundamentals
Lecture_4_Demo.ipynb
Sample Auto Essay Scoring model
NLP application demo with model evaluation metrics
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