Python for Data Science | Beginner Friendly Full Course in 5 Hours

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 Projects:

Other projects

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
4:45:46 - 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!

Happy coding!
Nick

P.s. Let me know how you go and drop a comment if you need a hand!

[slvatre]

it took me like two weeks but i finally got through this tutorial :) love your channel, keep it going

[mocabeentrill]

Hi Nick. Just finished this python for beginners course. It's professionally compiled, explained thoroughly and adequately. Thanks for comprehensively curating the basics on python . Blessings!

[cripthereaper]

You are the most amazing content creator, entertaining and educational, simple but clean.
Overall amazing, praying for your succes!

[urbxomp]

Dear Nicholas, thank you so much for sharing this video. After watching it, I feel much more confident in learning Python and the fundamental concepts necessary for data science.

[aimenbaig]

Hey dude! just discovered your channel, the content here is insanely amazing. I am an hour into this course now. I really needed this! Love it

[goadyjerry]

MAN I BELIEVE YOU SHOULD BE A PROFESSOR OF COMPUTER SCIENCE, I JUST LIKE THE WAY YOU TEACH

[Jackson_rw]

Man, thank you so much Nick. I have been struggling with learning python until I found this little beauty. You Legend!

[kevincdurand]

Im learning something new everytime I watch your videos. Fantastic work!

[morenomt]

why am I finding this channel just today?! This is the best!

[saharnazeri]

Amazingggg that is exactly what i am looking for

[bellemarravelo]

Hi sir, thanks for sharing codes and please make more videos about codes, it would be helpful
for students out their, like me but I graduated now, so hopefully keep sharing and we gain some knowledge from you...

[MM-unwg]

This an excellent video - Great work Nicholas

[Anbrinx]

Thank you so much Sir. I'm trying to learn data science. Your lecture helped me a lot. I want to exell in NumPy & Pandas. Lord Almighty Bless you Sir.

[jayparth]

You are such a gem, Nicholas Sir. Much thanks for this free enlightenment ✨

[Hosam_]

I really appreciate you and the course; it's amazing. I have one question about the projects. Could you recommend an order in which we should study these projects or videos? What order would be the most beneficial for us?

[namangoyal]

Thank you so much nick for this video. Helped a ton.

[abrh]

Love the guide! Looking forward for more these!
Keep up

[flutterflowhack]

Your explainations are so good. I didnt know anything regarding python but im able to follow through. Tank you for repettition and emphasis. Because of your video, I am posistive I can be a data scientist again.

[anabelamiranda]

Excellent. Such amazing explanations! Thank you so much.

[venugowda]

Hey bro Awesome content, I am looking for an internship and wanted to enter the data science field. Could you please share to how to start with the projects like where exactly to find the projects? (How long does it take to get a better grasp on this?)