Practical Data Science

Course Curriculum

Chapter 1: What is Data Science?

Lecture 1: Introduction

Lecture 2: The Process

Chapter 2: Python Basics

Lecture 1: Python Installation

Lecture 2: Jupyter (formerly iPython) Introduction

Lecture 3: NumPy

Lecture 4: Matplotlib

Lecture 5: Pandas

Chapter 3: Statistical Methods → Data Summarization

Lecture 1: Data Types (Part 1) — Identifying Types of Variables

Lecture 2: Data Types (Part 2) — Summarizing Variables Numerically

Lecture 3: Descriptive Statistics (in Python)

Lecture 4: Descriptive Statistics (in Excel)

Lecture 5: Descriptive Statistics (in SAS)

Chapter 4: Statistical Methods → Exploratory Data Analysis

Lecture 1: Analyzing Individual Variables — Histograms

Lecture 2: Analyzing Individual Variable — Probability Mass Functions

Lecture 3: Analyzing Individual Variable — Cumulative Distribution Functions

Lecture 4: Probability Density Functions & Modelling Empirical Distribution

Lecture 5: Smoothing Variable Distribution — Kernel Density Estimation

Lecture 6: Relationship Between Two Variables — Box Plots

Lecture 7: Relationship Between Two Variables — Scatter Plots

Lecture 8: Relationship Between Two Variables — Correlation & Covariance

Lecture 9: Bivariate Relationship Between Categorical Variables

Chapter 5: Exploratory Data Analysis (EDA) → Practical Example

Lecture 1: Exploratory Data Analysis of The Titanic Disaster

Chapter 6: Statistical Methods → Statistical Analysis

Lecture 1: Central Limit Theorem

Lecture 2: Estimation

Lecture 3: Linear Algebra and Matrices — Basics

Lecture 4: Linear Algebra and Matrices — Summary Statistics

Lecture 5: Parametric Statistical Analysis — Linear Response Models

Lecture 6: Linear Regression

Lecture 7: Linear Algebra and Matrices — Ordinary Least Squares

Chapter 7: Application of Statistical Methods

Lecture 1: Multiple Regression (in Excel)

Lecture 2: Linear Regression (in Python)

Lecture 3: Multiple Regression (in Python)

Chapter 8: Information Retrieval Using Query Language

Lecture 1: Getting Started with SQL

Lecture 2: CREATE TABLE Statement — Creating a Table in Database

Lecture 3: SELECT & LIMIT — Selecting Data from Database

Lecture 4: ORDER BY — Sorting Query Output

Lecture 5: GROUP BY — Grouping Output

Chapter 9: Big Data

Lecture 1: Data Integration — Introduction to HDF (Hierarchical Data Format)

Lecture 2: Data Integration — A Practical Example

Lecture 3: Data Integration — A Practical Example (Update)

Chapter 10: Data Science for Business & Marketing

Lecture 1: Product Promotion (in Python)