Data Science

Data Science

Dr. Emily Carter

AI Research Scientist

Module 1 :Data Science Fundamentals

  • What is Data Science?
  • Lifecycle of a Data Science Project
  • Roles: Data Analyst vs Data Scientist vs ML Engineer
  • Real-World Applications (Healthcare, Finance, Retail, etc.)

Module 2: Mathematics & Statistics for Data Science

  • Descriptive & Inferential Statistics
  • Probability, Distributions, Hypothesis Testing
  • Linear Algebra (Vectors, Matrices)
  • Calculus basics (Gradient, Derivatives in ML)

Module 3: Python for Data Science

  • Python Basics: Loops, Functions, Data Types
  • NumPy & Pandas for data handling
  • Matplotlib & Seaborn for visualization
  • Jupyter Notebooks for exploratory analysis

Module 4: Machine Learning

  • Supervised Learning: Regression, Classification
  • Unsupervised Learning: Clustering, Dimensionality Reduction
  • Confusion Matrix Accuracy, ROC-AUC
  • Scikit-learn, XGBoost

  • Model Evaluation:

    • Confusion Matrix

    • Accuracy, ROC-AUC

Module 5: Generative AI in Data Science

  • Introduction to LLMs (ChatGPT, Gemini)

  • Use of GenAI for:

    • Data cleaning suggestions

    • Auto-generating EDA summaries

    • Report writing

    • Prompt-based code generation

  • Hands-on with:

    • OpenAI API

    • Copilot for ML tasks

Module 6: Capstone Projects

End-to-End ML Project (choose from):

  • Fraud Detection

  • Customer Churn

  • Loan Prediction

  • Data Collection → EDA → ML → Reporting
  • GitHub Portfolio
  • Peer Review & Presentation

Tools Covered

  • Python, Pandas, NumPy, Scikit-learn
  • Power BI / Tableau
  • Jupyter, Google Colab
  • SQL for Data Science
  • TensorFlow / Keras
  • ChatGPT, Copilot, OpenAI API
  • Streamlit, GitHub

$199

Join Class

Class Features

  • Full-Stack Data Science Training: From fundamentals to real-world projects covering the complete data lifecycle
  • End-to-End Machine Learning: Build models for regression, classification, and clustering using Scikit-learn and XGBoost
  • Hands-On Coding with Python: Learn NumPy, Pandas, Matplotlib, Seaborn, and Jupyter Notebooks for data analysis
  • Certification Provided: Get a verified certificate upon successful completion

FAQS

Frequently Asked Question

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