What You'll Learn
- Real-world use cases of Python and its versatility.
- Installation of Python on both Mac and Windows operating systems.
- Fundamentals of programming with Python, including variables and data types.
- Working with various operators in Python to perform operations.
- Handling data using essential data structures like lists, tuples, sets, and dictionaries.
- Utilizing functions and working with parameters and arguments.
- Employing filter, map, and zip functions for data processing.
- Exploring analytical and aggregate functions for data analysis.
- Using built-in functions for regular expressions and handling special characters and sets.
- Iterating over elements using for loops and while loops.
- Understanding the object-oriented programming (OOP) concepts and principles.
- Working with date and time classes, including TimeDelta for time manipulation.
- Fundamental concepts and importance of statistics in various fields.
- How to use statistics for effective data analysis and decision-making.
- Introduction to Python for statistical analysis, including data manipulation and visualization.
- Different types of data and their significance in statistical analysis.
- Measures of central tendency, spread, dependence, shape, and position.
- How to calculate and interpret standard scores and probabilities.
- Key concepts in probability theory, set theory, and conditional probability.
- Understanding Bayes' Theorem and its applications.
- Permutations, combinations, and their role in solving real-world problems.
- Practical knowledge of various statistical tests, including t-tests, chi-squared tests, and ANOVA, for hypothesis testing and inference.
Requirements
- Students should have a general understanding of how to operate a computer.
- Be comfortable with common tasks like file management and using a web browser.
- No Prior Programming Experience Required.
- Students should have Python installed on their computers.
- A positive attitude and a willingness to learn and explore new concepts are essential for getting the most out of this course.
- A basic understanding of mathematics, including algebra and arithmetic.
- Familiarity with fundamental concepts in data analysis and problem-solving.
- A willingness to learn and engage with statistical concepts and Python programming.
- Basic knowledge of Python is a plus but not mandatory, as introductory Python concepts will be covered in the course.
Who This Course is For
- Beginners with no prior programming experience.
- Students or professionals in various fields, including business, science, social sciences, and healthcare, who want to enhance their data analysis skills.
- Anyone interested in automating tasks or data analysis.
- Data analysts, researchers, and scientists seeking to strengthen their statistical foundations and Python programming skills.
- Anyone interested in gaining a deeper understanding of statistical concepts and their practical applications.
- Beginners with no prior statistical knowledge but with a curiosity to learn and apply statistical methods.
- Professionals looking to advance their career by acquiring valuable statistical and data analysis skills.
- Individuals preparing for standardized tests or exams that include statistical and data analysis components.
Your Instructor
Meritshot Academy
Providing Best-in-class Education and Upskilling Courses.
4.5 Instructor Rating
10,034 Reviews
164,135 Students
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