Python for Data Science: Beginner's Full Course in 5 Hours 🚀
Kickstart your data science journey with this beginner-friendly Python course! Perfect for newcomers and those exploring Machine Learning. Learn the essentials in just 5 hours!

Nicholas Renotte
140.7K views • Aug 14, 2021

About this video
Starting your data science journey?
Just dipping your toe into Machine Learning?
Not too sure how to get started with the wild world of Python?
I got you.
There’s a ton of stuff to learn when you’re just getting started with data science, but having a good foundation in Python will set you up for success. That being said there’s a lot of fluff that can derail you when you’re learning.
So I put this together.
This is everything I wish I would have learned when starting off my journey in Data Science. It’s all of the Python that I use in my day to day job and it’s more than enough to get you started!
In this video, you’ll learn:
1. How to setup your environment for Python
2. Fundamentals of coding with Python with a focus on Data Science Applications
3. Applications of Python for Data Science along with some practical Python projects
Link to Code: https://github.com/nicknochnack/PythonForDataScience
Link to Projects:
Project 1 - End to End Machine Learning: https://www.youtube.com/playlist?list=PLgNJO2hghbmjNrHZqplNMEpsW-QLFdvJV
Project 2 - Data Science Basics: https://www.youtube.com/playlist?list=PLgNJO2hghbmjpjt9sa2POi4U0a1-GGTlj
Project 3 - Deep Learning Summarization: https://youtu.be/TsfLm5iiYb4
Project 4 - Sentiment Analysis: https://youtu.be/szczpgOEdXs
Other projects
AI for Gaming: https://youtu.be/hCeJeq8U0lo
Object Detection: https://youtu.be/yqkISICHH-U
Chapters
0:00 - Start
1:16 - Why you should learn Python
6:08 - How to get started
6:59 - Installing Anaconda
11:42 - Starting Jupyter Notebooks
13:42 - Creating a Jupyter Notebook
16:10 - Jupyter Shortcuts
17:54 - Exporting Jupyter to .py
21:04 - Cell Types
23:16 - Working with Markdown
25:23 - Accessing Documentation
26:42 - Google Colab
28:40 - Watson Studio
33:23 - SECTION 2 Variables & Data Types
34:38 - CRUD
41:13 - Variables
47:18 - Data Types
49:09 - Strings
52:52 - Integers
54:55 - Floats
56:27 - Booleans
1:00:44 - Lists
1:05:28 - Tuples
1:12:43 - Sets
1:21:05 - Dictionaries
1:28:17 - CRUD for Lists
1:30:14 - Creating a List
1:31:33 - Reading a List Using Indexing
1:32:55 - Updating List Values
1:33:58 - Using .append()
1:34:57 - Using .insert()
1:39:21 - CRUD for Dictionaries
1:39:58 - Create a Dictionary
1:41:41 - Read from a Dictionary
1:42:46 - Accessing Dictionary .keys()
1:43:27 - Accessing Dictionary .values()
1:43:57 - Updating Dictionaries
1:46:50 - Deleting from a Dictionary
1:48:54 - SECTION 3 Conditions & Loops
1:52:23 - Conditions and Logic
1:54:47 - if Statement
2:02:54 - else Statement
2:05:28 - elif Statement
2:09:46 - in Statement
2:17:29 - for Loop
2:25:27 - continue, break, pass
2:32:32 - while Loop
2:39:59 - Looping through Dictionaries
2:48:28 - List comprehensions
2:52:00 - SECTION 4 Functions
2:55:59 - Defining Functions
3:02:36 - Positional Arguments
3:10:47 - Multiple Positional Arguments
3:15:34 - Looping with an Index
3:21:35 - Keyword Arguments
3:25:35 - Combining Positional and Keyword Args
3:32:11 - return Keyword
3:34:52 - lambda Functions
3:39:00 - SECTION 5 Classes
3:42:41 - Classes
3:44:52 - class Statement
3:45:45 - __init__ Method
3:47:01 - self keyword
3:49:02 - Assigning properties
3:49:34 - Creating an object
3:51:36 - Methods
4:03:03 - Class Inheritance
4:06:36 - Defining a Child Class
4:08:10 - Inheriting using the super() function
4:18:25 - SECTION 6 - Modules and Packages
4:21:45 - Modules
4:23:05 - Creating a helper module
4:25:42 - Importing modules
4:27:25 - Accessing Python Packages
4:29:00 - Working with APIs
4:32:02 - Installing packages with pip install
4:33:42 - Viewing installed packages with pip list
4:34:36 - Importing Packages
4:35:41 - Making API calls with requests.get()
4:45:46 - Parsing JSON
4:57:24 - SECTION 7 Files & Error handling
5:01:26 - Working with Files
5:02:32 - Writing Files using the with statement
5:07:04 - Reading from files
5:11:01 - Error Handling
5:14:26 - Using try except statements
5:19:37 - SECTION 8 Math and Projects
5:22:48 - Math in Python
5:24:54 - Math Operators
5:25:20 - Addition
5:26:01 - Subtraction
5:26:42 - Division
5:27:37 - Floor Division
5:29:06 - Modulus
5:31:28 - Multiplication
5:31:59 - Power
5:32:52 - Rounding with round()
5:34:15 - Absolute Values abs()
5:38:29 - Math Package
5:40:45 - Python Projects
Oh, and don't forget to connect with me!
LinkedIn: https://bit.ly/324Epgo
Facebook: https://bit.ly/3mB1sZD
GitHub: https://bit.ly/3mDJllD
Patreon: https://bit.ly/2OCn3UW
Join the Discussion on Discord: https://bit.ly/3dQiZsV
Happy coding!
Nick
P.s. Let me know how you go and drop a comment if you need a hand!
Just dipping your toe into Machine Learning?
Not too sure how to get started with the wild world of Python?
I got you.
There’s a ton of stuff to learn when you’re just getting started with data science, but having a good foundation in Python will set you up for success. That being said there’s a lot of fluff that can derail you when you’re learning.
So I put this together.
This is everything I wish I would have learned when starting off my journey in Data Science. It’s all of the Python that I use in my day to day job and it’s more than enough to get you started!
In this video, you’ll learn:
1. How to setup your environment for Python
2. Fundamentals of coding with Python with a focus on Data Science Applications
3. Applications of Python for Data Science along with some practical Python projects
Link to Code: https://github.com/nicknochnack/PythonForDataScience
Link to Projects:
Project 1 - End to End Machine Learning: https://www.youtube.com/playlist?list=PLgNJO2hghbmjNrHZqplNMEpsW-QLFdvJV
Project 2 - Data Science Basics: https://www.youtube.com/playlist?list=PLgNJO2hghbmjpjt9sa2POi4U0a1-GGTlj
Project 3 - Deep Learning Summarization: https://youtu.be/TsfLm5iiYb4
Project 4 - Sentiment Analysis: https://youtu.be/szczpgOEdXs
Other projects
AI for Gaming: https://youtu.be/hCeJeq8U0lo
Object Detection: https://youtu.be/yqkISICHH-U
Chapters
0:00 - Start
1:16 - Why you should learn Python
6:08 - How to get started
6:59 - Installing Anaconda
11:42 - Starting Jupyter Notebooks
13:42 - Creating a Jupyter Notebook
16:10 - Jupyter Shortcuts
17:54 - Exporting Jupyter to .py
21:04 - Cell Types
23:16 - Working with Markdown
25:23 - Accessing Documentation
26:42 - Google Colab
28:40 - Watson Studio
33:23 - SECTION 2 Variables & Data Types
34:38 - CRUD
41:13 - Variables
47:18 - Data Types
49:09 - Strings
52:52 - Integers
54:55 - Floats
56:27 - Booleans
1:00:44 - Lists
1:05:28 - Tuples
1:12:43 - Sets
1:21:05 - Dictionaries
1:28:17 - CRUD for Lists
1:30:14 - Creating a List
1:31:33 - Reading a List Using Indexing
1:32:55 - Updating List Values
1:33:58 - Using .append()
1:34:57 - Using .insert()
1:39:21 - CRUD for Dictionaries
1:39:58 - Create a Dictionary
1:41:41 - Read from a Dictionary
1:42:46 - Accessing Dictionary .keys()
1:43:27 - Accessing Dictionary .values()
1:43:57 - Updating Dictionaries
1:46:50 - Deleting from a Dictionary
1:48:54 - SECTION 3 Conditions & Loops
1:52:23 - Conditions and Logic
1:54:47 - if Statement
2:02:54 - else Statement
2:05:28 - elif Statement
2:09:46 - in Statement
2:17:29 - for Loop
2:25:27 - continue, break, pass
2:32:32 - while Loop
2:39:59 - Looping through Dictionaries
2:48:28 - List comprehensions
2:52:00 - SECTION 4 Functions
2:55:59 - Defining Functions
3:02:36 - Positional Arguments
3:10:47 - Multiple Positional Arguments
3:15:34 - Looping with an Index
3:21:35 - Keyword Arguments
3:25:35 - Combining Positional and Keyword Args
3:32:11 - return Keyword
3:34:52 - lambda Functions
3:39:00 - SECTION 5 Classes
3:42:41 - Classes
3:44:52 - class Statement
3:45:45 - __init__ Method
3:47:01 - self keyword
3:49:02 - Assigning properties
3:49:34 - Creating an object
3:51:36 - Methods
4:03:03 - Class Inheritance
4:06:36 - Defining a Child Class
4:08:10 - Inheriting using the super() function
4:18:25 - SECTION 6 - Modules and Packages
4:21:45 - Modules
4:23:05 - Creating a helper module
4:25:42 - Importing modules
4:27:25 - Accessing Python Packages
4:29:00 - Working with APIs
4:32:02 - Installing packages with pip install
4:33:42 - Viewing installed packages with pip list
4:34:36 - Importing Packages
4:35:41 - Making API calls with requests.get()
4:45:46 - Parsing JSON
4:57:24 - SECTION 7 Files & Error handling
5:01:26 - Working with Files
5:02:32 - Writing Files using the with statement
5:07:04 - Reading from files
5:11:01 - Error Handling
5:14:26 - Using try except statements
5:19:37 - SECTION 8 Math and Projects
5:22:48 - Math in Python
5:24:54 - Math Operators
5:25:20 - Addition
5:26:01 - Subtraction
5:26:42 - Division
5:27:37 - Floor Division
5:29:06 - Modulus
5:31:28 - Multiplication
5:31:59 - Power
5:32:52 - Rounding with round()
5:34:15 - Absolute Values abs()
5:38:29 - Math Package
5:40:45 - Python Projects
Oh, and don't forget to connect with me!
LinkedIn: https://bit.ly/324Epgo
Facebook: https://bit.ly/3mB1sZD
GitHub: https://bit.ly/3mDJllD
Patreon: https://bit.ly/2OCn3UW
Join the Discussion on Discord: https://bit.ly/3dQiZsV
Happy coding!
Nick
P.s. Let me know how you go and drop a comment if you need a hand!
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Video Information
Views
140.7K
Likes
3.8K
Duration
05:45:19
Published
Aug 14, 2021
User Reviews
4.7
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