Practical Python for AI Coding 1
Learn Python basics for AI: syntax, functions, and libraries. Build an AI coding environment.The course covers Python basics, data types and functions
Learn Python basics for AI: syntax, functions, and libraries. Build an AI coding environment.The course covers Python basics, data types and functions
This beginner-friendly course introduces Python programming for AI applications. Students learn essential syntax, functions, and libraries commonly used in AI coding. The course covers Python basics, data types, control structures, and functions, with a focus on practical AI applications. Learners will set up a local AI coding environment, enabling them to start AI modeling with Scikit-learn, TensorFlow, and Keras upon completion. No prior coding experience is required.
4.6
(76 ratings)
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English
Tiếng Việt
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What you'll learn
Set up a local AI coding environment using Anaconda and JupyterLab
Understand and apply basic Python syntax and coding rules
Work with various data types including integers, floats, and strings
Use control structures like if-statements and loops for program flow
Create and use functions in Python
Manipulate lists, tuples, and dictionaries for data storage and retrieval
Skills you'll gain
This course includes:
8.33 Hours PreRecorded video
7 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 7 modules in this course
This course provides a comprehensive introduction to Python programming with a focus on AI applications. It is designed for complete beginners and covers essential Python concepts and syntax. The curriculum starts with setting up an AI coding environment using Anaconda and JupyterLab. Students then progress through basic Python rules, data types, control statements, functions, and non-primitive data types like lists, tuples, and dictionaries. The course emphasizes practical coding skills and prepares learners to work with AI libraries such as Scikit-learn, TensorFlow, and Keras. By the end of the course, students will have a solid foundation in Python programming and be ready to explore more advanced AI and machine learning topics.
Preparation for coding : Setting up AI coding environment
Module 1 · 1 Hours to complete
Basic concepts and rules of Python coding
Module 2 · 1 Hours to complete
Primitive data types
Module 3 · 1 Hours to complete
Control statements and iteration
Module 4 · 1 Hours to complete
Creating functions
Module 5 · 1 Hours to complete
Non-primitive data types: Lists and tuples
Module 6 · 1 Hours to complete
Non-primitive data types: Dictionaries and sets
Module 7 · 1 Hours to complete
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Instructor
Academic Profile and Resources
Professor at the School of Business and Technology Management within the College of Business at KAIST, currently on sabbatical at UPM in Madrid, Spain. For more information, visit his homepage. He offers a KAIST MOOC on Practical Python for AI Coding, available in Korean. Additionally, two courses on Coursera are available: Practical Python for AI Coding 1 and Practical Python for AI Coding 2.
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4.6 course rating
76 ratings
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