Python for Data Analytics 101 (PD101)
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.
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.
Key skills you will learn
Sign up for Python for Data Analytics 101 (PD101), and develop these core skills:
- Python for Data Analysis (from basics)
- Computational and Algorithmic Thinking
- Analytical Thinking and Problem Solving
- Working with Data (collection, cleaning, preparation)
- Basic Data Analysis and Interpretation
- Data Storytelling and Communication
- Information Validation and Critical Thinking
- Foundations for AI and Machine Learning
Python for Data Science Track
200+
Python for Data Analytics 101 (PD101)
Beginner
5-6 weeks
English
Free (Core) & Paid (Pro )
Python for Data Analytics 101 (PD101)
This course teaches you how to use Python to work with data, perform basic analysis, and communicate insights effectively.
You will learn the core concepts, tools, and best practices used in data analytics, and understand how data supports decision-making and modern AI systems.
The course prepares you for entry-level roles and further learning paths in data analytics, AI, and data-driven professions.
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
Sign Up For FreePro
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
Get Pro AccessPython 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
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.
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.
What you will know after the course
By the end of the course, you will be able to:
- write and understand basic Python programs;
- work with common data structures such as lists and dictionaries;
- read, clean, and prepare simple datasets;
- perform basic data analysis and summarize results;
- use Python tools to explore and understand data;
- present insights clearly using simple reporting and storytelling techniques;
- understand how data supports decision-making and AI systems;
- build a foundation for further learning in data analytics, data science, and AI.