1

• Why Should you Learn to Write Programs?

2

• Understanding programming

3

• Types of Programming Languages

4

• Building Blocks and Terminologies

5

• Installing and Running Python

1

• Variables, Expressions, and Statements

2

• Conditional Execution

3

• Functions

4

• Iteration

5

• Lists

6

• Strings

7

• Dictionaries and Tuples

8

• Files

1

• Essential Python Libraries

2

• Jupyter Notebooks and Google Colaboratory

3

• Numpy Basics

4

• Pandas Basics

5

• Data Loading, Storage, and File Formats

6

• Data Wrangling

7

• Exploratory Data Analysis and Visualization

1

Introduction

2

Types of Variables

3

Sampling Techniques

4

Sample size

1

Introduce SPSS

2

Data coding, and data entry

3

Importing data to SPSS from excel

4

Data manipulation in SPSS

5

Data checking and editing in SPSS Introduction to descriptive statistics using SPSS

6

Measures of central tendency for different types of data

7

Measures of Variability for different types of data

8

One-way Tabulation distinct types of variables

9

Two-way and 3-way tabulations for distinct types of variables

1

Descriptive Statistics

2

Python Programming

3

Data Types and Operators

4

Data Structures

5

Control Flow

6

Functions

7

Scripting

8

Working with Data in Python

9

Data Analysis

10

Pandas and NumPy

11

Data Analysis Process

12

Data Mining

13

Data Wrangling

14

Assessing and Cleaning Data

15

Exploratory Data Analysis

16

Anomaly Detection

1

Introduction to Data Visualization Tools

2

Basic and Specialized Visualization

3

Matplotlib and Seaborn

4

Different Data Charts

5

Advanced Visualization Tools

6

Heat Maps Plotting

7

Word Cloud

8

Folium Maps

9

Intensity Maps

10

Geospatial Maps in Python

11

Choropleth Maps

1

Linear Regression

2

Logistic Regression

1

Explore US Bikeshare Data Use python to understand US bikeshare data. Calculate statistics and build an interactive environment where a user can choose the data and filter for a dataset to show.

1

House Sales in King County, USA Analyze and predict housing prices using attributes or features such as square footage, number of bedrooms, number of floors and so on

1

Audience Interest in Data Science Topics Use python to generate visualization plots to summarize the results of a survey that was conducted to gauge an audience interest in different data science topics

1

San Francisco Incidents Distribution Use python Folium maps to generate a Choropleth map of the crime rate in San Francisco, based on data for one year, and show distribution of different crimes’ type ities

1

• Descriptive Statistics

2

• Probability

3

• Normalization.

4

• Inferential Statistics

5

• Linear Algebra Review

1

• Introduction to Artificial Intelligence

2

• Introduction to Data Science

3

• Data Science life cycle.

4

• Introduction to Machine Learning & Data Mining

5

• Machine Learning

6

• Data Mining

7

• Supervised and Unsupervised Learning

8

• Types of Data

9

• Data Preprocessing

10

• Frequent Item Sets

11

• Association Rules & Apriori Algorithm

12

• Regression for Data Science

13

• Bias and Variance

14

• Base Classifiers for Data Science

15

• Clustering

16

• Evaluation of Learning Models for a Data Scientist

1

• Python Basics

2

• Python Data Structures

3

• Python Programming Fundamentals

4

• Data Science Libraries

1

• Project 1: Market Basket Analysis (Apriori)

2

• Project 2: Automotive Price Prediction (Linear Regression Algorithim)

3

• Project 3: Fraud Detection (Logistic Regression Algorithm)

4

• Project 4: Customer Churn Prediction (Neural Networks Algorithm)

5

• Project 5: Customer Segmentation (K-Means Clustering)