Edspark

— Curriculum —

12-Module Curriculum — Data Science with AI Built In

Every module teaches real data science skills + the exact AI tools professionals use for that skill in their daily work.

M1 — Foundations of Data Science

M2 — Setting Up Your Environment

M3 — Python for Data Science

M4 — Data Collection

M5 — Data Cleaning & Preprocessing

M6 — EDA & Statistics

M7 — Data Visualisation

M8 — Intro to Machine Learning

M9 — Supervised Learning

M10 — Unsupervised Learning

M11 — Deep Learning Intro

M12 — Capstone Project

Module 1 — Foundations of Data Science

Understand what data science is, how it works, and why every major company runs on it.

🔬 Core Topics

Overview of Data Science and its importance

Data Science workflow and stages

Core elements: gathering, cleaning, analysis, visualisation, ML, deployment

Real-world applications across industries

🤖 AI Integration NEW

Use ChatGPT to explore data science career paths and create a study roadmap

Perplexity AI for real-time case studies of data science in any industry

Use AI to compare data science roles: analyst vs scientist vs engineer

Gemini to summarise research papers and extract key data science concepts

TOOLS:ChatGPTPerplexity AIGoogle GeminiNotion AI

Module 2 — Setting Up Your Environment

Install and configure everything — Python, Jupyter, Anaconda, and the core libraries.

⚙️ Core Topics

Installing Python, Jupyter Notebook, and Anaconda

Configuring NumPy, Pandas, Matplotlib, Seaborn

Google Colab setup and cloud notebooks

Version control basics with Git and GitHub

🤖 AI Integration NEW

GitHub Copilot setup in VS Code and Jupyter Notebooks

Google Gemini in Colab — AI assistance directly inside your notebook

Use ChatGPT to debug environment setup errors instantly

AI to generate requirements.txt and environment config files

TOOLS:GitHub CopilotGemini in ColabChatGPTCodeium

Module 3 — Python for Data Science

Master the Python skills that every data scientist uses — lists, dicts, functions, and Pandas DataFrames.

🐍 Core Topics

Python data structures: lists, dicts, tuples

Functions, loops, and list comprehensions

NumPy arrays and vectorised operations

Pandas DataFrames: creation, indexing, operations

🤖 AI Integration NEW

GitHub Copilot to auto-complete Pandas operations as you type

ChatGPT Code Interpreter to explain any Python error in plain English

Use AI to generate Pandas cheat sheets and operation examples on demand

Codeium for faster Python coding with AI-powered autocomplete

TOOLS:GitHub CopilotChatGPTCodeiumGemini in Colab

Module 4 — Data Collection

Gather data from the web, APIs, and databases — the foundation of every data science project.

🌐 Core Topics

Web scraping with BeautifulSoup and Selenium

Consuming REST APIs with Python requests

Loading CSV, Excel, JSON, and SQL data

Kaggle datasets and open data sources

🤖 AI Integration NEW

Use ChatGPT to generate web scraping scripts from any URL description

GitHub Copilot to write API call and data extraction code instantly

AI to generate data collection pipelines from natural language requirements

Prompt Perplexity AI to find the best open datasets for any project idea

TOOLS:ChatGPTGitHub CopilotPerplexity AICodeium

Module 5 — Data Cleaning & Preprocessing

Real data is messy — learn to handle missing values, outliers, and feature engineering like a pro.

🧹 Core Topics

Managing missing data: imputation strategies

Outlier detection and treatment methods

Feature engineering and encoding

Normalisation, standardisation, and scaling

🤖 AI Integration NEW

ChatGPT Code Interpreter — upload a CSV, get a full cleaning report instantly

Julius AI for one-click AI-powered data profiling and missing value analysis

GitHub Copilot to write complete data preprocessing pipelines

Use AI to generate feature engineering suggestions for any domain

TOOLS:ChatGPT Code InterpreterJulius AIGitHub Copilot

Module 6 — EDA & Statistics

Find patterns before modelling — statistical thinking and exploratory data analysis done right.

📊 Core Topics

Descriptive statistics and data distributions

Correlation analysis and feature relationships

Hypothesis testing basics

EDA workflow with Pandas and Matplotlib

🤖 AI Integration NEW

ChatGPT to interpret statistical test results in plain English

Julius AI — natural language EDA: "show me correlations" on any dataset

Gemini in Colab for inline AI explanations of statistical patterns

Use AI to auto-generate EDA reports and data quality summaries

TOOLS:Julius AIChatGPTGemini in ColabNoteable AI

Module 7 — Data Visualisation

Communicate insights visually — from basic Matplotlib to interactive Plotly dashboards.

📈 Core Topics

Matplotlib: line, bar, scatter, histogram, boxplot

Seaborn: heatmaps, pairplots, categorical charts

Plotly for interactive visualisations

Storytelling with data — design principles

🤖 AI Integration NEW

Julius AI — describe any chart in plain English, get the code instantly

ChatGPT to generate Plotly dashboards from dataset descriptions

GitHub Copilot for auto-completing Seaborn and Matplotlib chart code

Use AI to write insight narratives for any visualisation

TOOLS:Julius AIChatGPTGitHub CopilotNoteable AI

Module 8 — Intro to Machine Learning

Understand how machines learn — types of ML, the ML pipeline, and Scikit-learn fundamentals.

🤖 Core Topics

Supervised, unsupervised, reinforcement learning

The ML pipeline: data → model → evaluation → deploy

Train/test split and cross-validation

Scikit-learn API and model selection

🤖 AI Integration NEW

ChatGPT to explain any ML algorithm with visual analogies

GitHub Copilot to generate complete Scikit-learn pipelines

Use AI to compare model options for any given data problem

Gemini in Colab for inline ML concept explanations while coding

TOOLS:ChatGPTGitHub CopilotGemini in ColabCodeium

Module 9 — Supervised Learning

Regression and classification — predict outcomes and classify data with real datasets.

📐 Core Topics

Linear and logistic regression

Decision Trees and Random Forests

SVM and K-Nearest Neighbours

Model evaluation: accuracy, F1, ROC-AUC

🤖 AI Integration NEW

ChatGPT to generate hyperparameter tuning code for any Scikit-learn model

GitHub Copilot to write feature importance analysis and model comparison code

Use AI to interpret model evaluation metrics in business-friendly language

Weights & Biases AI for experiment tracking and model versioning

TOOLS:ChatGPTGitHub CopilotW&B AICodeium

Module 10 — Unsupervised Learning

Find hidden patterns without labels — clustering, dimensionality reduction, and anomaly detection.

🔍 Core Topics

K-Means clustering and cluster evaluation

Hierarchical and DBSCAN clustering

PCA for dimensionality reduction

Anomaly detection basics

🤖 AI Integration NEW

ChatGPT to explain cluster analysis results in business context

Julius AI for instant AI-generated clustering visualisations

GitHub Copilot to generate PCA and t-SNE visualisation code

Use AI to write customer segmentation reports from clustering results

TOOLS:ChatGPTJulius AIGitHub Copilot

Module 11 — Deep Learning Intro

Neural networks, TensorFlow, Keras — understand how AI systems actually learn.

🧠 Core Topics

Neural network architecture and forward propagation

Backpropagation and gradient descent explained

TensorFlow and Keras: build your first neural network

CNNs for image classification basics

🤖 AI Integration NEW

ChatGPT to explain neural network concepts with step-by-step analogies

GitHub Copilot to generate Keras model architectures from descriptions

Hugging Face for pre-trained models and transfer learning

Use AI to debug training loops and interpret loss curves

TOOLS:ChatGPTGitHub CopilotHugging FaceGemini in Colab

Module 12 — Capstone Project

Apply everything — collect, clean, analyse, model, and present a complete data science project.

🎯 Core Topics

End-to-end project: problem definition to deployment

Project documentation and GitHub README

Model deployment with Streamlit or Flask

Portfolio presentation and LinkedIn showcase

🤖 AI Integration NEW

ChatGPT to write full project documentation and README files

GitHub Copilot for building Streamlit deployment code

Use AI to generate LinkedIn project write-ups and portfolio descriptions

AI to prepare mock interview answers about your capstone project

TOOLS:ChatGPTGitHub CopilotGeminiNotion AI

— Career Outcomes —

Jobs You Can Get After This Workshop

Data science is the #1 most valued tech skill globally. Here are the roles this workshop directly prepares you for.

🔬

Data Scientist

₹7 – 22 LPA

Build ML models, conduct EDA, and present data-driven insights to product and business teams at top companies.

PythonScikit-learnSQL

Demand

Very High

📊

Data Analyst

₹4 – 12 LPA

Clean, analyse, and visualise datasets to find patterns. The most accessible high-paying entry-level role in tech right now.

SQLTableauPython

Demand

🔥 Hot Role

⚙️

ML Engineer

₹9 – 25 LPA

Take data science models and turn them into production systems. High demand at AI startups and product companies.

TensorFlowMLOpsPython

Demand

Very High

🤖

AI Engineer

₹12 – 30 LPA

Build AI-powered products using LLMs, Hugging Face, and cloud AI APIs. The fastest-growing role in the data field.

LLMsHugging FaceAPIs

Demand

🚀 Emerging

🔍

Research Analyst

₹5 – 14 LPA

Apply data science to research problems in finance, healthcare, and government. Growing fast in India.

StatisticsPythonExcel

Demand

High

🏗️

Data Engineer

₹8 – 20 LPA

Build data pipelines and warehouses that data scientists rely on. High demand at every company with large datasets.

SparkSQLCloud

Demand

Very High

Data Science
Workshop with GenAI

Everything You Need to Think Like a Data Scientist

End-to-End Data Science Skills

AI in Every Module

Python & Libraries Hands-On

Certification That Stands Out

The Career That Pays More Every Year

12-Module Curriculum — Data Science with AI Built In

Build Real Data Science Projects

AI-Powered EDA Report

Customer Churn ML Model

Deployed ML Web App

AI Tools You Will Learn & Use