Python for Data Science with Assignments
A Comprehensive and Practical Hands-On Guide to Learning Python for Beginners, Aspiring Developers, Self-Learners, etc.
4.50 (177 reviews)
24 091
students
9.5 hours
content
Jan 2024
last update
$54.99
regular price
What you will 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.
5429784
udemy ID
07/07/2023
course created date
27/07/2023
course indexed date
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