Statistics with Python
About This Course
This course on Statistics with Python is perfect for anyone interested in analysing and interpreting data. It will cover the basic concepts of statistics and will teach you how to use the Python programming language to perform statistical analysis. You will learn how to visualise your data and draw meaningful conclusions from it.
This course offers an introduction to the use of Python for statistical analysis. It covers both descriptive and inferential statistics, providing learners with the skills to analyze data and draw meaningful conclusions. Through this course, learners will gain an understanding of how to use Python to explore and visualize data, develop models, and interpret the results.
Learning Objectives
Material Includes
- Datasets
Requirements
- Basic understanding of statistics concepts and terminology
- Familiarity with Python programming language
- Knowledge of data manipulation and analysis using libraries such as pandas and numpy
- Understanding of mathematical operations and calculations
- Comfort with working with datasets and performing data exploration
- Prior experience in statistical analysis is helpful but not required
Target Audience
- Data analysts
- Business analysts
- Researchers
- Data scientists
- Professionals working with data and seeking to enhance their statistical analysis skills
- Individuals interested in using Python for statistical analysis
- Students or academic professionals in fields related to statistics or data analysis
Curriculum
Basics of Statistics
Descriptive Statistics
Probability Distributions
Confidence Intervals
STAP001
Advanced Statistics
Your Instructors
Edulearnia
R&D Engineer
I am in love with artificial intelligence, machine learning, deep learning and especially data science. I like challenges and a job well done. I am sure to participate in the local and international development of artificial intelligence. I like reading, writing, soft music. I like to be in a friendly relationship with my entourage, I like to be helpful.
Material Includes
- Datasets
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