Practical Python for AI Coding 2
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There are 5 modules in this course
Introduction video : https://youtu.be/TRhwIHvehR0
This course is for a complete novice of Python coding, so no prior knowledge or experience in software coding is required. This course selects, introduces and explains Python syntaxes, functions and libraries that were frequently used in AI coding. In addition, this course introduces vital syntaxes, and functions often used in AI coding and explains the complementary relationship among NumPy, Pandas and TensorFlow, so this course is helpful for even seasoned python users. This course starts with building an AI coding environment without failures on learners’ desktop or notebook computers to enable them to start AI modeling and coding with Scikit-learn, TensorFlow and Keras upon completing this course. Because learners have an AI coding environment on their computers after taking this course, they can start AI coding and do not need to join or use the cloud-based services.
What's included
6 videos1 assignment
6 videos•Total 83 minutes
- Differences among list, NumPy, Pandas and TensorFlow•8 minutes
- Basic concepts of arrays: Data type, shape, and dimension•17 minutes
- Special arrays and array indexing•19 minutes
- Array operatins and broadcasting rule•15 minutes
- Slicing and flattening arrays•14 minutes
- Getting summary statistics•9 minutes
1 assignment•Total 20 minutes
- Week 1 Quiz•20 minutes
What's included
7 videos1 assignment
7 videos•Total 115 minutes
- Introducing Pandas library and Series•13 minutes
- DataFrames: creation and index change•10 minutes
- DataFrames slicing•12 minutes
- Sorting DataFrames data•10 minutes
- DataFrame exercise with Iris data•32 minutes
- Combining DataFrames based on unique ID•20 minutes
- Descriptive statistics and one hot vector•18 minutes
1 assignment•Total 20 minutes
- Week 2 Quiz•20 minutes
What's included
5 videos1 assignment
5 videos•Total 75 minutes
- String concept, indexing and slicing•12 minutes
- String concatenation and splitting•11 minutes
- Advanced string slicing•15 minutes
- Character into ASCII code and f-strings•19 minutes
- Reading and saving data files•19 minutes
1 assignment•Total 20 minutes
- Week 3 Quiz•20 minutes
What's included
6 videos1 assignment
6 videos•Total 112 minutes
- Preparing canvas and adding subplots•21 minutes
- Line graphs and bar charts•22 minutes
- Drawing histograms•23 minutes
- Scatter plot, box plot and pie chart•21 minutes
- Drawing with DataFrame data•10 minutes
- Plotting with Seaborn•15 minutes
1 assignment•Total 20 minutes
- Week 4 Quiz•20 minutes
What's included
3 videos1 assignment
3 videos•Total 49 minutes
- Concept of object oriented programming and creating a class•26 minutes
- Class inheritance and overriding methods•13 minutes
- Another example of class inheritance and closing remarks•10 minutes
1 assignment•Total 20 minutes
- Week 5 Quiz•20 minutes
Instructor
Explore more from Software Development
- Status: PreviewK
Korea Advanced Institute of Science and Technology(KAIST)
Course
- Status: PreviewD
DeepLearning.AI
Course
- Status: Free Trial
Guided Project
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Reviewed on Jun 29, 2022
The content is easy to follow from the scratch, and the content is very essential for data engineering. If there is a basic explanation and example for object oriented programming, it will be better.
Reviewed on Apr 1, 2022
A nice syllabus of Python course. And the quizs are nice to enjoy.Thank you professor and Coursera community.
Reviewed on Jan 22, 2024
I would recommend this course to any programming beginner, not only for python
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