Course Description

Python Programming for AI, Data Science & Embedded Systems is a hands-on, beginner-friendly course designed to equip learners with practical programming skills essential for artificial intelligence, data analysis, and embedded system development. Python serves as the foundation of this course, enabling students to write programs, manipulate data, and visualize results efficiently.
Through structured exercises and projects, learners will gain confidence in Python programming, build practical knowledge of numerical computing, data handling, and visualization, and acquire a solid base to advance into AI, machine learning, and embedded system projects.
By the end of this course, learners will be able to independently write Python programs, handle real-world datasets, and apply their skills to a variety of technical domains.

What you will learn

• Python
  
• Numpy
• Pandas
  
• Matplotlib

Course Objectives

• Enable learners to write and run Python programs independently.
• Teach the fundamental programming constructs used in AI and embedded systems.
  
• Provide skills to handle numerical data efficiently using NumPy.
• Equip learners to clean, transform, and analyze datasets using Pandas.
• Introduce learners to data visualization techniques using Matplotlib.
• Build a strong foundation for advanced AI, machine learning, and embedded systems projects.
  

Key Highlights

• Hands-on exercises for real-world application of concepts.
• Learn Python for AI, data science, and embedded systems.
  
• Step-by-step guidance from Python basics to library usage.
• Projects and exercises integrated with Raspberry Pi and Linux.
• Flexible, self-paced learning with structured support.
  

Learning Outcomes

By the end of this course, learners will be able to:

• Write and execute Python programs independently.
• Implement programming constructs such as loops, conditionals, and functions.
• Manipulate numerical data efficiently with NumPy arrays.
• Analyze, clean, and transform datasets using Pandas.
• Visualize data trends using Matplotlib.
• Apply foundational Python skills in AI, machine learning, and embedded systems development.
  

Who Should Enroll

• Diploma or Engineering students (ongoing or completed).
• Technologists, educators, hobbyists, and professionals interested in AI and data science.

Who This Course Is For

This program is built for learners who are serious about gaining real, practical skills in Python Programming—not just completing a syllabus. The focus is on learning-by-doing, building confidence, and developing the ability to design and implement working Python applications.
This is not a passive classroom experience. Instead, students are expected to engage actively, solve problems, build prototypes, and apply the concepts taught. The instructor provides guidance, mentorship, and structured direction—but the actual learning happens through individual effort, experimentation, and persistence.
While a certificate is awarded upon completion, the true value of this course lies in the skills, mindset, and hands-on experience gained. Those who commit to the process will walk away with the confidence to build systems, troubleshoot issues, and contribute to real-world product development.

Prerequisites

To participate effectively in this course, learners must have a smartphone with at least 2.5GB of data available per day.
Additionally, learners should have a laptop with an Intel i3 or i5 processor, running either Windows or Linux, to write and run code, perform simulations, and complete assignments. If it has a GPU, the better. Finally, learners will need a USB storage ranging from 32GB to 1TB. The storage can be an SD card, SATA SSD or NVME with a suitable USB reader.

• Familiar with coding concepts.
  
• Computer proficiency.
  

Pricing and Enrollment

To begin your enrollment process, simply visit our Contact Page and submit your details. Please include a preferred time for us to reach you. Once received, our team will get in touch with you to share the course pricing, available batch schedules, and the next steps for enrollment.