By the end of this course, you will be able to
Code with Python programming language and identify how to use Python functional programming. Then, you will learn about the most advanced Python foundations.
Identify how to structure data using collection containers and handle data with Python libraries. Then, you will extract and analyze data from different resources.
Build Python solutions for data science, perform data analysis with Pandas, data visualization using matplotlib, and advanced visualization with Seaborn.
Course details
- 6 h 7 m/69 lessons
- Last updated: 1/5/2023
- Course completion certificate
Course Content
Course Intro
Variables and Types Tutorial
Installing tools
Describe what's inside the code
Markdown in Jupyter tutorial
4 Using Jupyter Notebook to code with Python
Use Anaconda Prompt
Course Intro
Installing tools
Markdown in Jupyter tutorial
4 Using Jupyter Notebook to code with Python
Use Anaconda Prompt
Variables and Types Tutorial
Describe what's inside the code
Define Blocks and Avoid IndentationError
String full tutorial
Numbers, Math and f-string tutorial
Handling inputs and outputs
Structure Data using lists
Structure data using tuples
Structure Data using Dictionaries
Structure Data using sets
Comparing Values
output from Logics
Conditional Statements
The while loop
The for loop in Python
Python Library Functions
User-Defined Functions
The Lambda Power
break statement
continue statement
for else statement
App to Put all together
Core Python OOP
Exploring Inheritance
Comprehensions
Constructed modules and random
Doing mathematics
Doing statistics
Errors Exploration
Exceptions Playground
IO data in memory
Interacting with operating system data
Moving data files between directories
Data will be in the trash bin
Zipping and Unzipping Data
NumPy Level 1
NumPy Level 2
NumPy Level 3
NumPy Level 4
NumPy Level 5
NumPy Level 6
NumPy Level 7
NumPy Level 8
NumPy Level 9
Pandas data analysis level 1
Pandas data analysis level 2
Pandas data analysis level 3
Pandas data analysis level 4
Pandas data analysis level 5
Pandas data analysis level 6
Matplotlib data visualization part1
Matplotlib data visualization part2
Matplotlib data visualization part3
Matplotlib data visualization part4
Matplotlib data visualization part5
Matplotlib data visualization part6
Matplotlib data visualization part7
Seaborn statistical graphs level 1
Seaborn statistical graphs level 2
Seaborn statistical graphs level 3
Seaborn statistical graphs level 4
Seaborn statistical graphs level 5
Seaborn statistical graphs level 6
Seaborn statistical graphs level 7
About this course
Data science is a vast field, and one of the very rewarding, and it is increasing in expansion day by day, due to its great importance and benefits, as it is the future. Data science enables companies to measure, track, and record performance metrics for facilitating and enhancing decision-making. Companies can analyze trends to make critical decisions to engage customers better, improve company performance, and increase profitability. One of the most powerful programming languages ââused for Data science is Python, an easy and powerful language, and that will be covered throughout the course.
Course requirements and prerequisites
There are no requirements for this course. Your interest in the topic and your commitment to learning are all you need to achieve the utmost benefit from this course.
Mentor
Ahmed El Mohandes
Software Development Engineer | Instructor and Expert in Software Engineering and Data Science
1,451 Learners
11 Courses
