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Empowering Data Vision: Data Science Course

Week 1: From Python to Exploring Data with Pandas.

Day 1: Course Methodology, Tools, Setup, and Review.

Session 1: Development Environment

  1. Operating Systems

  2. Terminal

  3. Python version

  4. PIP or Anaconda

  5. Visual Studio Code

Session 2: Python Setup and or review

  1. Using the Python REPL (Read, Evaluate, Print, Loop)

  2. Basic Data types

  3. Inspecting data types

  4. Grouping data types

  5. Modules

  6. Numpy Review or Introduction

  7. Pandas Hello world

Day 2: From Spread sheet to Pandas

Session 1: Excel and Pandas terminology

  1. Introduction

  2. Excel verses Pandas Terminology and example.

Session 2: Introduction to Pandas

  1. Panda data types

  2. Series

  3. Data Frames

Session 3: Putting it all together

  1. Review of Excel sheet

  2. Steps to Reproduce with pandas.

  3. Saving the data in different forms.

  4. Check output in Excel.

Day 3: Data Manipulation with Pandas

Session 1: Loading Data and Exploring data in Pandas

  1. Reading Simple created XLS into Pandas

  2. Getting started with Exploratory Data Analysis (EDA)

Session 2: Large dataset EDA

  1. Getting data set Penguins.

  2. Exploring data set

  3. clean up data functions

Manipulating data

  1. Sorting

  2. filter

  3. creating new columns

  4. Group by

Day 4: Data Manipulation with Pandas

Session 1: Advanced EDA

  1. GapMinder.

  2. Basic EDA and Cleanup.

  3. Join

  4. Merge

  5. Data transformation

  6. Mutation

session 2: Class EDA of different Data sets.

Week 2 Visualization of Data

Day 1: Bar Plots and Histograms

Session 1: Bar Plots

  1. Definitions, description, and components.

  2. Use cases for bar charts.

  3. Load data

  4. Explore and choose the data

  5. Create a Bar plot

Practical Exercise bar Plots
  1. Hands on Exercise

Session 2: Histograms

  1. Definitions, description and components.

  2. Use case for Histograms.

  3. Load data

  4. Explore and choose the data

  5. Create a Histogram

Practical Exercise histogram
  1. Hands on Exercise

Day 2: Line Plots and Scatter Plots

Session 1: Line Plots

  1. Definitions and Components:

  2. Use cases for line plots.

  3. EDA and Setup of data.

  4. Create Line plot

Practical Exercise
  1. Hands on Exercise

Session 2: Scatter Plots

  1. Definitions, description, and Components

  2. Use cases for scatter plots.

  3. EDA and Setup of data.

  4. Create Scatter plot

Practical Exercise on Scatter Plots
  1. Hands-on Exercise:

Day 3: Box plots and Heat Maps

Session 1: Box Plots

  1. Definitions, description, and Components:

  2. Use cases for box plots.

  3. EDA and Setup of data.

  4. Create Box plot

Practical Exercise on Box Plots
  1. Hands-on Exercise:

Session 2: Heat Maps

  1. Definitions, description, and Components:

  2. Use cases for Heat Maps

  3. EDA and Setup of data.

  4. Create Heat map

Practical Exercise for Heat Map
  1. Hands-on Exercise:

Day 4: Advanced Visualizations and other data sets

Session 1: Anscombe's Quartet

  1. Definitions and Significance:

  2. Plotting Anscombe's Quartet.

Session 2: Using live data

  1. EDA and selecting data

  2. Picking the right Plot

Session 3: Questions, Comments, and Wrapup