Python Basics for Data Science
Learn essential Python programming skills for data science, including data analysis, visualization, and basic scripting in this beginner-friendly course.
Learn essential Python programming skills for data science, including data analysis, visualization, and basic scripting in this beginner-friendly course.
This comprehensive course introduces Python programming with a focus on data science applications. Students will progress from basic Python concepts to hands-on data analysis using Jupyter notebooks. The course covers fundamental programming concepts, data structures, file handling, and popular libraries like Pandas and Numpy. With IBM Watson Studio integration, learners gain practical experience in data visualization and analysis. The course emphasizes hands-on learning through lab exercises, preparing students to create their own Python scripts and perform basic data analysis. Suitable for beginners, it provides a solid foundation in Python programming while focusing on real-world data science applications.
4.4
(833 ratings)
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What you'll learn
Learn Python programming fundamentals and syntax for data science applications
Master essential data structures and basic algorithms in Python
Work with popular data science libraries including Pandas and Numpy
Develop proficiency in using Jupyter notebooks for code development
Gain hands-on experience in data analysis and visualization
Learn to access and manipulate data using APIs and web scraping techniques
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 5 modules in this course
This comprehensive Python course is designed for beginners entering the field of data science. The curriculum covers Python fundamentals, data structures, programming concepts, and practical data analysis tools. Students learn to work with popular libraries like Pandas and Numpy, use Jupyter notebooks for development, and handle data through file operations and APIs. The course emphasizes hands-on learning through lab exercises, enabling students to write their own Python scripts and perform basic data analysis. Integration with IBM Watson Studio provides real-world experience in data visualization and analysis.
Python Basics
Module 1
Python Data Structures
Module 2
Python Programming Fundamentals
Module 3
Working with Data in Python
Module 4
Working with Numpy Arrays
Module 5
Fee Structure
Instructor
Pioneering Data Scientist Bridging AI Research and Education
Dr. Joseph Santarcangelo, a Data Scientist at IBM, brings a unique blend of academic excellence and practical expertise to the field of data science and artificial intelligence. With a Ph.D. in Electrical Engineering, his groundbreaking research focused on the intersection of machine learning, signal processing, and computer vision to understand how video content influences human cognitive processes. At IBM, he has established himself as a prominent educator and course developer, creating comprehensive learning materials that have reached hundreds of thousands of students worldwide. His teaching portfolio encompasses a wide range of technical subjects, from foundational Python programming to advanced topics in artificial intelligence, machine learning, and computer vision. Santarcangelo's ability to translate complex technical concepts into accessible learning experiences has made him an influential figure in data science education, maintaining consistently high ratings from learners while continuing to push the boundaries of applied machine learning and artificial intelligence research.
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4.4 course rating
833 ratings
Frequently asked questions
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