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Data Science with Python Programming - Course Syllabus
1. Introduction to Data Science
Introduction to Data Science
Python in Data Science
Why is Data Science so Important?
Application of Data Science
What will you learn in this course?
2. Introduction to Python Programming
What is Python Programming?
History of Python Programming
Features of Python Programming
Application of Python Programming
Setup of Python Programming
Getting started with the first Python program
3. Variables and Data Types
What is a variable?
Declaration of variable
Data types in Python
Checking Data type
Data types Conversion
Python programs for Variables and Data types
4. Python Identifiers, Keywords, Reading Input, Output Formatting
What is an Identifier?
Taking multiple inputs from user
Python end parameter
5. Operators in Python
Operators and types of operators
- Arithmetic Operators
- Relational Operators
- Assignment Operators
- Logical Operators
- Membership Operators
- Identity Operators
- Bitwise Operators
Python programs for all types of operators
6. Decision Making
Introduction to Decision making
Types of decision making statements
Introduction, syntax, flowchart and programs for
- if statement
- if…else statement
- nested if
Introduction to Loops
Types of loops
- for loop
- while loop
- nested loop
Loop Control Statements
Break, continue and pass statement
Python programs for all types of loops
Accessing Values in Lists
Deleting List Elements
Basic List Operations
Built-in List Functions and Methods for list
9. Tuples and Dictionary
Accessing, Deleting Tuple Elements
Basic Tuples Operations
Built-in Tuple Functions & methods
Difference between List and Tuple
Accessing, Updating, Deleting Dictionary Elements
Built-in Functions and Methods for Dictionary
10. Functions and Modules
What is a Function?
Defining a Function and Calling a Function
Ways to write a function
Types of functions
What is a module?
Creating a module
11. Working with Files
Opening and Closing Files
The open Function
The file Object Attributes
The close() Method
Reading and Writing Files
More Operations on Files
12. Regular Expression
What is a Regular Expression?
re.match() vs re.search()
13. Introduction to Python Data Science Libraries
Data Science Libraries
Libraries for Data Processing and Modeling
Libraries for Data Visualization
14. Components of Python Ecosystem
Components of Python Ecosystem
Using Pre-packaged Python Distribution: Anaconda
15. Analysing Data using Numpy and Pandas
Analysing Data using Numpy & Pandas
What is numpy? Why use numpy?
Installation of numpy
Examples of numpy
What is ‘pandas’?
Key features of pandas
Python Pandas - Environment Setup
Pandas – Data Structure with example
Data Analysis using Pandas
16. Data Visualisation with Matplotlib
Data Visualisation with Matplotlib
- What is Data Visualisation?
- Introduction to Matplotlib
- Installation of Matplotlib
Types of data visualization charts/plots
- Line chart, Scatter plot
- Bar chart, Histogram
- Area Plot, Pie chart
- Boxplot, Contour plot
17. Three-Dimensional Plotting with Matplotlib
Three-Dimensional Plotting with Matplotlib
- 3D Line Plot
- 3D Scatter Plot
- 3D Contour Plot
- 3D Surface Plot
18. Data Visualisation with Seaborn
Introduction to seaborn
Different categories of plot in Seaborn
Exploring Seaborn Plots
19. Introduction to Statistical Analysis
What is Statistical Analysis?
Introduction to Math and Statistics for Data Science
Terminologies in Statistics – Statistics for Data Science
Categories in Statistics
Mean, Median, and Mode
20. Data Science Methodology (Part-1)
Module 1: From Problem to Approach
Module 2: From Requirements to Collection
Module 3: From Understanding to Preparation
21. Data Science Methodology (Part-2)
Module 4: From Modeling to Evaluation
Module 5: From Deployment to Feedback
22. Introduction to Machine Learning and its Types
What is a Machine Learning?
Need for Machine Learning
Application of Machine Learning
Types of Machine Learning
- Supervised learning
- Unsupervised learning
- Reinforcement learning
23. Regression Analysis
Implementing Linear Regression
Multiple Linear Regression
Implementing Multiple Linear Regression
Implementing Polynomial Regression
What is Classification?
Implementing Logistic Regression
Implementing Decision Tree
Support Vector Machine (SVM)
What is Clustering?
How does K-Means Clustering work?
Implementing K-Means Clustering
Agglomerative Hierarchical clustering
How does Agglomerative Hierarchical clustering Work?
Divisive Hierarchical Clustering
Implementation of Agglomerative Hierarchical Clustering
26. Association Rule Learning
Association Rule Learning
Working of Apriori algorithm
Implementation of Apriori algorithm
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