Learn and build your Python Programming skills from the ground up in addition to Python Data Science libraries and tools
Note: Course Free for limited time and limited users(500 limit) so Enroll ASAP. If not free it means you are late. Scroll Down and click Enroll Now button to get enrolled
This course includes:
- 6 hours on-demand video
- 2 articles
- 11 downloadable resources
- Access on mobile and TV
- Full lifetime access
- Certificate of completion
Scroll Down and click Enroll Now Button to get enrolled into the Free Course
What you’ll learn
- Code with Python Programming Language
- Python Functional Programming
- Structure Data using collection containers
- Object-Oriented Design
- Advanced Python Foundations
- Handling Data with Python Libraries
- Numerical Python
- Extracting and Analyzing data from different resources
- Data Analysis with Pandas
- Data Visualization using matplotlib
- Advanced Visualization with Seaborn
- Build Python solutions for data science
- Get Instructor QA Support and help
Course content
13 sections • 76 lectures • 6h 10m total lengthCollapse all sections
Mastering Python, Data Handling, Analysis and Visualization5 lectures • 19min
- Welcome to Data Science: Python for Data Analysis 2022 Full BootcampPreview01:40
- Download and Install the working toolsPreview01:20
- Jupyter Overview + Markdown in Jupyter tutorialPreview06:46
- Using Jupyter Notebook for coding with PythonPreview05:41
- Using Anaconda Prompt03:14
- Quiz 13 questions
The Basics of Python6 lectures • 53min
- Variables and Types Tutorial10:37
- Describe what’s inside the code04:44
- Define Blocks and Avoid IndentationError04:19
- Strings full tutorial13:43
- Numbers, Math and f-string tutorial15:13
- Handling inputs and outputs04:29
- Quiz 27 questions
Python Data Structures4 lectures • 47min
- Structure Data using lists21:02
- Structure data using tuples10:31
- Structure Data using Dictionaries08:04
- Structure Data using sets07:21
- Quiz 38 questions
The Fundamentals of Python12 lectures • 1hr 15min
- Comparing Values08:36
- Output from Logics06:48
- Conditional Statements08:55
- The while loop in Python02:56
- The for loop in Python07:18
- Python Library Functions11:21
- User-Defined Functions07:30
- The lambda power08:50
- The break statement04:05
- The continue statement04:34
- The for else statement02:14
- Program to Put all together01:43
- Quiz 45 questions
OOP in Python2 lectures • 22min
- Core Python OOP: Classes and Instances12:01
- Core Python OOP: Exploring Inheritance10:10
- Quiz 55 questions
Advanced Foundations6 lectures • 33min
- Concise Comprehensions05:52
- Constructed modules and random06:37
- Doing mathematics04:46
- Doing statistics04:17
- Errors Exploration04:28
- Exceptions Playground06:44
- Quiz 64 questions
Python Data Handling5 lectures • 26min
- IO data in memory07:11
- Interacting with operating system data03:03
- Moving data files between directories04:41
- Data will be in the trash bin04:16
- Zipping and Unzipping Data06:49
- Quiz 74 questions
Numerical Python – NumPy9 lectures • 38min
- NumPy Level 107:09
- NumPy Level 205:03
- NumPy Level 302:25
- NumPy Level 403:44
- NumPy Level 505:38
- NumPy Level 603:49
- NumPy Level 703:46
- NumPy Level 803:19
- NumPy Level 903:07
- Quiz 86 questions
Analyze Data with Pandas6 lectures • 22min
- Pandas data analysis level 103:49
- Pandas data analysis level 204:41
- Pandas data analysis level 302:18
- Pandas data analysis level 403:31
- Pandas data analysis level 502:52
- Pandas data analysis level 604:30
- Quiz 95 questions
Visualize Data with Matplotlib7 lectures • 18min
- Matplotlib data visualization level 102:57
- Matplotlib data visualization level 201:31
- Matplotlib data visualization level 303:05
- Matplotlib data visualization level 403:13
- Matplotlib data visualization level 501:36
- Matplotlib data visualization level 603:01
- Matplotlib data visualization level 702:32
- Quiz 102 questions
Advanced Data graphs with Seaborn8 lectures • 16min
- Seaborn statistical graphs level 103:41
- Seaborn statistical graphs level 201:56
- Seaborn statistical graphs level 301:16
- Seaborn statistical graphs level 401:39
- Seaborn statistical graphs level 502:30
- Seaborn statistical graphs level 602:30
- Seaborn statistical graphs level 701:49
- Seaborn statistical graphs level 800:10
Resources5 lectures • 3min
- Python Programming00:39
- NumPy00:28
- Pandas00:24
- Matplotlib00:35
- Seaborn00:28
BONUS SECTION1 lecture • 1min
- Bonus00:11
Requirements
- No Python prior experience is required to take this Training
- Computer and Internet access
Description
Hello and welcome to Data Science: Python for Data Analysis Full Bootcamp.
Data science is a huge field, and one of the promising fields that is spreading in a fast way. Also, it is 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, enhance company performance, and increase profitability.
And the employment of data science and its tools depends on the purpose you want from them.
For example, using data science in health care is very different from using data science in finance and accounting, and so on. And I’ll show you the core libraries for data handling, analysis and visualization which you can use in different areas.
One of the most powerful programming languages that are used for Data science is Python, which is an easy, simple and very powerful language with many libraries and packages that facilitate working on complex and different types of data.
This course will cover:
- Python tools for Data Analysis
- Python Basics
- Python Fundamentals
- Python Object-Oriented
- Advanced Python Foundations
- Data Handling with Python
- Numerical Python(NumPy)
- Data Analysis with Pandas
- Data Visualization with Matplotlib
- Advanced Graphs with Seaborn
- Instructor QA Support and Help
HD Video Training + Working Files + Resources + QA Support.
In this course, you will learn how to code in Python from the beginning and then you will master how to deal with the most famous libraries and tools of the Python language related to data science, starting from data collection, acquiring and analysis to visualize data with advanced techniques, and based on that, the necessary decisions are taken by companies.
I am Ahmed Ibrahim, a software engineer and Instructor and I have taught more than 500,000 engineers and developers around the world in topics related to programming languages and their applications, and in this course, we will dive deeply into the core Python fundamentals, Advanced Foundations, Data handling libraries, Numerical Python, Pandas, Matplotlib and finally Seaborn.
I hope that you will join us in this course to master the Python language for data analysis and Visualization like professionals in this field.
We have a lot to cover in this course.
Let’s get started!
Who this course is for:
- Python beginners and newbies
- Data Scientist who knows other language tools
- New Python Data Analysts
- Data Science Beginners
- New developers and Programmers
- Programmers and developers who know other programming language but are new to python
- Anyone who wants to use Python for data analysis and visualization in a short time!
Note: The course is free for a limited time and limited to 500 users. Enroll as soon as possible. If it is no longer free, it means you are late, and it has already exceeded its limits.
