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Python Programming Specialization

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Course Outline Download
Reading Material Notes.docx
Cheat Sheet Download
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1

Python Fundamental

  • Overview of Python
  • Install Python
  • Install Python IDE
  • Code Your First Python Script
  • Comment
  • Number
  • String
  • List
  • Tuple
  • Dictionary
  • Set
  • Arithmetic Operators
  • Compound Operators
  • Comparison Operators
  • Membership Operators
  • Logical Operators
  • Conditional
  • Loop
  • Iterating Over Multiple Sequences
  • Comprehension
  • Function Syntax
  • Return Values
  • Default Arguments
  • Variable Arguments
  • Lambda, Map, Filter
  • Import Modules and Packages
  • Python Standard Packages
  • Third Party Packages
 Exercises:
2

Python Intermediate

  • Comprehension Syntax
  • Types of Comprehension
  • Generator Syntax
  • Types of Generators
  • Read and Write Data to Files
  • Manage File and Folders with Python OS Module
  • Manage Paths with Python Pathlib Module
  • Introduction to Object Oriented Programming
  • Create Class and Objects
  • Method and Overloading
  • Initializer & Destructor
  • Inheritance
  • Polymorphism
  • Setup SQLite3 Database
  • Apply CRUD Operations on SQLite3
  • Integration to External Databases
  • Exceptions versus Syntax Errors
  • Handle Exceptions with Try and Except Blocks
  • The Else Clause
  • Clean Up with Finally
 Exercises:
3

Python Data Analytics and Visualization

  • Data Analytics with Pandas
  • Pandas DataFrame and Series
  • Import and Export Data
  • Filter and Slice Data
  • Clean Data
  • Join Data
  • Transform Data
  • Aggregate Data
  • Data Visualization with Matplotlib and Seaborn
  • Visualize Statistical Relationships with Scatter Plot
  • Visualize Categorical Data with Bar Plot
  • Visualize Correlation with Pair Plot and Heatmap
  • Visualize Linear Relationships with Regression
  • Statistical Data Analysis
  • Time Series Analysis
  • Data Piping
  • Groupby and Apply Custom Functions
  • Linear Regression
 Exercises:
4

Python Statistical Analysis

  • Mean & Medium
  • Standard Deviation & Variance
  • Percentiles
  • Summary
  • What is Seaborn?
  • Visualizing Statistical Relationships with Scatter Plot
  • Visualizing Categorical Data with Bar Plot
  • Visualizing Correlation with Pair Plot and Heatmap
  • Visualizing Linear Relationships with Regression
  • What is Hypothesis Testing?
  • T Statistics
  • Student's t-test
  • What is Statistical Modeling?
  • Statistical Modeling with StatsModel
  • Goodness of Fit
  • ANOVA
  • Bayesian Inference
  • Using PyMC3 for Bayesian Inference
 Exercises:
Numpy:
Scipy:
Matplotlib:
Pandas:
Seaborn:
PyMC:
5

Python Web API with Flask

  • What is Flask?
  • Request Response Cycle
  • Create a Simple Flask API
  • Debug Mode
  • Routing
  • Testing the API on Postman
  • JSON Format
  • Jsonify the Data
  • HTTP Methods and Status Code
  • Add Status Code to the Data
  • Variable Rules
  • Test Out URL Rules on Postman
  • Database
  • ORM and SQLAlchemy
  • Define Table and Data
  • Serialize Data with Marshmallow
  • Create a Register Form
  • Login
  • Authentication with JSON Web Token (JWT)
  • Read Data
  • Add Data
  • Update Data
  • Delete Data
 Flask:

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