Data Science with Python Course Syllabus
Course Syllabus
Download SyllabusIntroduction of Python
- Why do we need Python?
- Program structure
Execution Steps
- Interactive Shell
- Executable or script files
- User Interface or IDE
Data types in Python
- Memory management and Garbage collections
- Object creation and deletion
- Object properties
Data Types and Operations
- Numbers
- Strings
- List
- Tuple
- Dictionary
- Other Core Types
Loops and expression in Python
- Assignments, Expressions and prints
- Statements and Syntax
- If tests and Syntax Rules
- While and For Loops
- Iterations and Comprehensions
User defined function in Python
- Functions
- Function definition and call
- Function Scope
- Arguments
- Function Objects
- Anonymous Functions
Exception handling in Python
- Exception Handling
- Default Exception Handler
- Catching Exceptions
- Raise an exception
- User defined exception
Data Science Data Science and AI
- All the topics in data science will covered with following concept:
- All the topics in data science will covered with following concept:
- Mathematics beside of each model
- Which scenario we want to use a particular algorithm
- How to apply it in tool
- An inferential thing of each model
Difference between each model
- Introduction to Machine Learning & Predictive Modelling
- Major Classes of Learning Algorithms -Supervised vs Unsupervised Learning
Statistics
- Standard Deviation
- Variance
- Concept of hypothesis testing
- T-test
- Chi-square
- Anova
- Correlation
- Probability
- Outliers
- Drop highly correlated features
Acquire the necessary skills for a prosperous career in data science, students will learn how to use Python’s robust libraries to gather, clean, analyze, visualize, and model data with our python with data science syllabus.
