Practical Python for AI Coding 2
- Offered byCoursera
Practical Python for AI Coding 2 at Coursera Overview
Duration | 9 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Practical Python for AI Coding 2 at Coursera Highlights
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
Practical Python for AI Coding 2 at Coursera Course details
- 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.
Practical Python for AI Coding 2 at Coursera Curriculum
Numpy library: Using arrays
Differences among list, NumPy, Pandas and TensorFlow
Basic concepts of arrays: Data type, shape, and dimension
Special arrays and array indexing
Array operatins and broadcasting rule
Slicing and flattening arrays
Getting summary statistics
Week 1 Quiz
Pandas library: Using DataFrames
Introducing Pandas library and Series
DataFrames: creation and index change
DataFrames slicing
Sorting DataFrames data
DataFrame exercise with Iris data
Combining DataFrames based on unique ID
Descriptive statistics and one hot vector
Week 2 Quiz
Strings and files
String concept, indexing and slicing
String concatenation and splitting
Advanced string slicing
Character into ASCII code and f-strings
Reading and saving data files
Week 3 Quiz
Data visualization: matplotlib and seaborn
Preparing canvas and adding subplots
Line graphs and bar charts
Drawing histograms
Scatter plot, box plot and pie chart
Drawing with DataFrame data
Plotting with Seaborn
Week 4 Quiz
Object oriented programming: introducing class object
Concept of object oriented programming and creating a class
Class inheritance and overriding methods
Another example of class inheritance and closing remarks
Week 5 Quiz
Practical Python for AI Coding 2 at Coursera Admission Process
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