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SR-PYTHON.AA1
Python
Self-paced · 1 year access
35 Hands-On LiveLabs
Practice real IT tasks in guided environments.
- Real environments
- Auto-graded
- No installation
01 / Lessons & labs
See exactly what you will learn and practice
Lessons
9 Interactive Lessons01 Introduction to Python 23 LiveLab +
23 LiveLab in this lesson — see the labs panel →
02 Descriptive Statistics 2 LiveLab +
2 LiveLab in this lesson — see the labs panel →
03 NumPy 2 LiveLab +
2 LiveLab in this lesson — see the labs panel →
04 Probability Distribution 1 LiveLab +
1 LiveLab in this lesson — see the labs panel →
05 Pandas 3 LiveLab +
3 LiveLab in this lesson — see the labs panel →
06 Data Visualization with Matplotlib.pyplon & Seaborn 1 LiveLab +
1 LiveLab in this lesson — see the labs panel →
07 Inferential Statistics and Hypothesis Testing 2 LiveLab +
2 LiveLab in this lesson — see the labs panel →
08 Hypothesis Testing - One Sample Test +
09 Hypothesis Testing - Two Sample Tests, ANOVA, GoF & Contingency Tables 1 LiveLab +
1 LiveLab in this lesson — see the labs panel →
Hands-On Labs Our edge
35 LiveLabs- Getting Started with Jupyter Notebook
- Working with Variables
- Using the input() Function
- Using the round() Function
- Working with Operators
- Displaying the Multiplication Table Using Loops
- Calculating the Square Root
- Getting Started with Visual Studio Code
- Using Conditional Statements
- Working with the if Statement
- Using Loops
- Using the for Loop and the range Function
- Working with Functions and Classes
- Using Custom Exception Class in Python
- Working with Function Arguments
- Using a lambda Expression
- Working with Lists
- Arranging and Presenting Data Using Dictionaries
- Combining Dictionaries
- Storing Company Employee Table Data Using a List and a Dictionary
- Working with Dictionaries
- Working with Tuples
- Finding the Mean and Median from a Collection of Income Data
- Performing Descriptive Statistics Using Python
- Finding the Inter Quartile Range
- Creating Two-Dimensional Array Using NumPy
- Filtering Array using NumPy
- Generating Random Numbers to Simulate the Probability
- Using the Pandas Library
- Creating a Correlation Heat Chart
- Working with Files
- Plotting a Histogram
- Performing Hypothesis Testing
- Performing Z-Test
- Conducting ANOVA
Labs run in your browser — nothing to install.
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Prepare for Python
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- 1 year of full access
- 35 LiveLab included
- Certificate of completion
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