Python for Data Analytics 101 (PD101)

BERJAYA Python for Data Science Track

Start your journey into data analysis, learn how to work with data using Python, and build a strong foundation for the PCED™ – Certified Entry-Level Data Analyst with Python certification.

Course Details

Beginner

5 Weeks

English

Free (Core) & Paid ( Pro)

900+ people already enrolled

Core

5 modules

40+ lessons

hands-on labs,

interactive exercises,

real-life data analysis scenarios, quizzes, and tests,

a Diploma of Course Completion,

a 20% discount code for the PCED™ certification exam.

Free

Pro

5 modules

40+ lessons

hands-on labs,

interactive exercises,

real-life data analysis scenarios, quizzes, and tests,

a Diploma of Course Completion,

a 20% discount code for the PCED™ certification exam.

$49

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About
Course Overview
Pro
Edube Sandbox

About the course

This beginner-friendly course introduces you to both Python programming and data analysis from the ground up. You will learn how to work with real-world data, understand how it is structured, and apply Python to collect, clean, organize, analyze, and present data in a clear and meaningful way.

In today’s AI-driven world, data is the foundation of everything – from dashboards to machine learning models. This course helps you understand how data becomes information and how information becomes insight, giving you the essential skills needed to work with modern technologies.

By completing this course, you will be prepared to take the PCED™ – Certified Entry-Level Data Analyst with Python certification and take your first step toward careers in data analytics, AI, business intelligence, and technology.

This course is structured to help you learn both conceptually and practically. As you move through the modules, you will build knowledge, apply it in hands-on activities, and check your understanding along the way. Here’s what you can expect:

Modules – the course is divided into five structured modules, each focused on a major stage of the data analytics workflow.
Lessons – each module contains focused, step-by-step lessons that introduce concepts in a clear and beginner-friendly way.
Interactive Features – in the premium version, lessons include quizzes, coding tasks, and practice activities to help you apply what you learn.
Module Projects – at the end of each module, you will complete a practical project based on realistic data scenarios.
Module Tests – each module ends with a test that helps you assess your understanding before moving on.
Final Assessment – at the end of the course, you will complete a final assessment that brings together the most important skills and concepts from the full course.

Python for Data Analytics 101 (PD101) is designed for anyone who wants to understand how data works in today’s world.
It will particularly appeal to:

beginners with little or no experience in Python or data analytics who want to start learning from scratch

learners interested in data analysis, AI, and modern technology who want to understand the foundational role of data

students and early-career professionals preparing for entry-level roles such as data analyst, reporting assistant, or business intelligence support

anyone who wants to develop critical thinking skills and understand how information is created, validated, and interpreted

professionals in non-technical roles (e.g., managers, product owners) who want to better understand data-driven processes and communicate effectively with technical teams

Prerequisites

There are no prerequisites for this course. It is fully self-contained and introduces both Python programming and data analysis concepts step by step.

Associated Certification

Prior Experience Recommended:

PCED-30-0x

Certified Entry-Level Data Analyst with Python

PCAD-31-0x

Certified Associate Data Analyst with Python

Course Overview

Here’s an overview of the course structure:

Understanding what data is, how it is classified, where it comes from, how it moves through its lifecycle, and how analytics supports decision-making, including ethical and legal considerations.

Building core programming skills using variables, data types, strings, conditionals, loops, functions, and data structures like lists and dictionaries.

Working with files and CSV data, cleaning messy datasets, handling missing and invalid values, and preparing data for analysis.

Applying aggregations, descriptive statistics, NumPy tools, and exploratory data analysis (EDA) techniques to understand data.

Designing clear visuals, interpreting charts, telling data stories, and presenting insights effectively to different audiences.

Go Pro for Hands-on Practice & Course Diploma

The Pro version of the course includes a Diploma of Course Completion and gives you access to 40+ hands-on labs, interactive exercises, and quizzes designed to reinforce your learning and help you apply concepts in real-world scenarios. It also supports your preparation for the PCED™ certification exam by providing practical experience aligned with exam objectives.

Get Pro Access