Python Programming for Beginners and Data SciencePublished 6/2026
Created by Krithika V
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner |
Genre: eLearning |
Language: English |
Duration: 82 Lectures ( 45h 8m ) |
Size: 22.5 GB
Python⚡ Develop Python applications using fundamental and advanced programming concepts.
⚡ Analyze and manipulate datasets using NumPy and Pandas.
⚡ Create professional visualizations using Matplotlib and Seaborn.
⚡ Apply Data Science techniques and basic Machine Learning models to solve real-world problems.
⚡ Develop practical projects using Python for data-driven applications.
⚡ Perform exploratory data analysis and derive meaningful insights from data.
⚡ Build a strong foundation for advanced careers in Data Analytics, Data Science, and AI.
Requirements❗ Programming knowledge is not required to attend this course
DescriptionThis comprehensive course is designed for absolute beginners, students, researchers, engineers, professionals, and anyone interested in developing practical programming and data analysis skills using Python.
Python has become one of the most widely used programming languages in the world due to its simplicity, versatility, and extensive ecosystem of libraries. It is the preferred language for Data Science, Artificial Intelligence, Machine Learning, Data Analytics, Automation, Scientific Computing, and many other emerging technologies. This course provides a structured learning path that takes you from the fundamentals of Python programming to essential Data Science concepts and applications.
The course begins with Python basics, including variables, data types, operators, decision-making statements, loops, functions, modules, and file handling. Learners will gain hands-on experience in writing Python programs and solving practical problems using efficient coding techniques.
As the course progresses, you will explore Python data structures such as lists, tuples, dictionaries, and sets, which are essential for managing and processing data effectively. You will also learn exception handling and best programming practices that help in developing robust and reliable applications.
A significant portion of the course is dedicated to Data Science fundamentals. You will learn how to perform numerical computations using NumPy and analyze real-world datasets using Pandas. Through practical examples and case studies, you will gain experience in data cleaning, preprocessing, transformation, filtering, grouping, and aggregation techniques that are commonly used by data professionals.
The course also introduces data visualization using Matplotlib and Seaborn, enabling you to create informative charts, graphs, and dashboards that communicate insights effectively. Finally, you will gain an overview of the Data Science workflow and basic Machine Learning concepts, preparing you for advanced studies in Data Analytics, Machine Learning, and Artificial Intelligence.
Throughout the course, learners will work on hands-on exercises, coding demonstrations, and mini-projects that reinforce concepts and provide practical experience in solving real-world problems using Python and Data Science tools.
Who this course is for⭐ Beginners in Python
⭐ Begineers in Data Science
⭐ Students / Academic / any professional learners
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