Introduction to Python Programming for Absolute Beginners

Welcome to "Introduction to Python Programming for Absolute Beginners"!

Are you ready to unlock the power of coding but don’t know where to start? This course is designed especially for you — no prior experience needed! Whether you dream of building apps, analyzing data, automating tasks, or simply understanding the language behind today's technology, Python is the perfect first step.

Python is one of the most beginner-friendly, versatile, and in-demand programming languages in the world. Through clear explanations, practical examples, and hands-on exercises, you’ll learn the foundations of Python programming in a supportive and accessible environment. By the end of this course, you'll not only write your own programs with confidence, but you'll also gain a strong base to continue your journey into the exciting world of technology and innovation in the era of digitalization all around, big data, machine learning (ML) and artificial intelligence (AI).

Join us and take your first step into programming — your future in tech starts here!

This first course on Python was designed as a 6-day course on weekends to accommodate your time, with 4-hour sessions each day, totaling 24-hour of learning and applications.

 

We present the course content below for your review:

Session 1: Getting Started with Python (2 Hours)

• Understand the purpose of Python and its applications.

• Install Anaconda and launch Jupyter Notebook.

• Write and execute basic Python scripts in Jupyter Notebook.

 

Session 2: Python Data Types and Variables (2 Hours)

• Learn about data types: integers, floats, strings, and booleans.

• Understand variables and type conversion.

 

Session 3: Collections in Python (2 Hours)

• Learn about lists, tuples, sets, and dictionaries.

• Perform basic operations on collections.

 

Session 4: Conditional Statements and Loops (2 Hours)

Learning Objectives:

• Learn conditional statements (if, elif, else).

• Understand and implement loops (for, while).

 

Session 5: Functions in Python (2 Hours)

• Understand the purpose of functions.

• Define and call functions with arguments and return values.

 

Session 6: File Handling in Python (2 Hours)

• Learn to read and write files in Python.

• Understand file modes (r, w, a).

 

Session 7: Introduction to Pandas (6 Hours)

Session 7.1: Getting Started with Pandas

• Handling Missing Data

• Data Exploration and Descriptive Statistics

• Loading Data into pandas

 

Session 7.2: Data Exploration and Manipulation

• Exploratory Data Analysis

• Selecting and Filtering Data

• Sorting Data

• Handling Missing Values

 

Session 7.3: Aggregation and Grouping

• Aggregation Basics

• Grouping Data

Session 7.4: Advanced Data Cleaning and Visualization

• Advanced Data Cleaning

• Visualizing Data

 

Session 7.5: Date Column Manipulations in a DataFrame

• Parsing and Converting Dates

• Extracting Date Components

• Filtering and Querying by Date

• Resampling and Aggregating Time-Series Data

 

Session 8: Data Visualization with Matplotlib (2 Hours)

• Create basic visualizations such as line, bar, and scatter plots.

• Customize plots with titles, labels, legends, and styles.

• Save plots as image files.

 

Session 9: Introduction to NumPy (2 Hours)

• Learn about NumPy arrays and their advantages over Python lists.

• Perform basic array operations, slicing, and indexing.

• Understand broadcasting and its applications.

 

Session 10: Final EDA Project (2 Hours)

• Apply all learned skills to analyze and visualize real-world datasets.