Step into the world of programming with our 5 Days Python Programming Specialization course. This course is crafted for those aspiring to master Python, one of the most versatile and in-demand programming languages in the tech industry. Over the course of five days, you will be immersed in an intensive learning experience, covering the fundamentals of Python, from basic syntax and control structures to complex functions and modules. Our curriculum is designed to build a solid foundation, whether you're a beginner or looking to refine your skills.

In this specialization, you will explore the practical applications of Python in various domains such as data analysis, web development, and automation. The course highlights include hands-on projects and real-world scenarios that will equip you with the skills needed to solve complex problems efficiently. By the end of this course, you will not only understand the core concepts of Python programming but also be able to apply them in creating robust and scalable applications. This is more than just a programming course; it's a gateway to advancing your career in tech, preparing you to tackle challenges and seize opportunities in the fast-evolving digital landscape.

Certificate

All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.

Funding and Grant

HRD Corp Claimable for Employers Registered with HRD Corp

Course Code: M1250

Day 1
Topic 1: Python Fundamental

Topic 1.1 Get Started on Python

• Overview of Python

• Install Python

• Install Python IDE

• Code Your First Python Script

• Comment

Topic 1.2: Data Types

• Number

• String

• List

• Tuple

• Dictionary

• Set

Topic 1.3 Operators

• Arithmetic Operators

• Compound Operators

• Comparison Operators

• Membership Operators

• Logical Operators

Topic 1.4 Control Structure, Loop and Comprehension

• Conditional

• Loop

• Iterating Over Multiple Sequences

• Comprehension

Topic 1.5 Function

• Function Syntax

• Return Values

• Default Arguments

• Variable Arguments

• Lambda, Map, Filter

Topic 1.6 Modules & Packages

• Import Modules and Packages

• Python Standard Packages

• Third Party Packages

Day 2
Topic 2: Python Intermediate

Topic 2.1 Comprehensions & Generators

• Comprehension Syntax

• Types of Comprehension

• Generator Syntax

• Types of Generators

Topic 2.2 File and Directory Handling

• Read and Write Data to Files

• Manage File and Folders with Python OS Module

• Manage Paths with Python Pathlib Module

Topic 2.3 Object Oriented Programming

• Introduction to Object Oriented Programming

• Create Class and Objects

• Method and Overloading

• Initializer & Destructor

• Inheritance

• Polymorphism

Topic 2.4 Database

• Setup SQLite3 Database

• Apply CRUD Operations on SQLite3

• Integration to External Databases

Topic 2.5 Error Handling Using Exception

• Exceptions versus Syntax Errors

• Handle Exceptions with Try and Except Blocks

• The Else Clause

• Clean Up with Finally

Day 3
Topic 3: Python Data Analytics and Visualization

Topic 3.1 Data Preparation

• Data Analytics with Pandas

• Pandas DataFrame and Series

• Import and Export Data

• Filter and Slice Data

• Clean Data

Topic 3.2 Data Transformation

• Join Data

• Transform Data

• Aggregate Data

Topic 3.3 Data Visualization

• 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

Topic 3.4 Data Analysis

• Statistical Data Analysis

• Time Series Analysis

Topic 3.5 Advanced Data Analytics

• Data Piping

• Groupby and Apply Custom Functions

• Linear Regression

Topic 1 Descriptive Statistics

• Mean & Medium

• Standard Deviation & Variance

• Percentiles

• Summary

Topic 2.1: Data Visualization with Seaborn

• 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

Topic 2.3 Hypothesis Testing with SciPy

• What is Hypothesis Testing

• T Statistics

• Student's t-test

Day 4
Topic 4: Python Statistical Analysis

Topic 4.1 Descriptive Statistics

• Mean & Medium

• Standard Deviation & Variance

• Percentiles

• Summary

Topic 4.2: Data Visualization with Seaborn

• 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

Topic 4.3 Hypothesis Testing with SciPy

• What is Hypothesis Testing

• T Statistics

• Student's t-test

Topic 4.4 Statistical Modeling with StatsModel

• What is Statistical Modeling

• Statistical Modeling with StatsModel

• Goodness of Fit

• ANOVA

Topic 4.5 Bayesian Inference with PyMC3

• Bayesian Inference

• Using PyMC3 for Bayesian Inference

Day 5
Topic 5: Python Web API with Flask

Topic 5.1 Get Started on Flask API

• What is Flask?

• Request Response Cycle

• Create a Simple Flask API

• Debug Mode

• Routing

• Testing the API on Postman

Topic 5.2 Returned Data from API

• JSON Format

• Jsonify the Data

• HTTP Methods and Status Code

• Add Status Code to the Data

• Variable Rules

• Test Out URL Rules on Postman

Topic 5.3: Working with Database

• Database

• ORM and SQLAlchemy

• Define Table and Data

• Serialize Data with Marshmallow

Topic 5.4: API Security

• Create a Register Form

• Login

• Authentication with JSON Web Token (JWT)

Topic 5.5: Read, Create, Update and Delete

• Read Data

• Add Data

• Update Data

• Delete Data