Data Analysis with Python Course - Numpy, Pandas, Data Visualization

Learn the basics of Python, Numpy, Pandas, Data Visualization, and Exploratory Data Analysis in this course for beginners. This was originally presented as a live course.

By the end of the course, you will be able to build an end-to-end real-world course project and earn a verified certificate of accomplishment. There are no prerequisites for this course.

This full course video includes 6 lectures (all in this video):
• Introduction to Programming with Python
• Next Steps with Python
• Numerical Computing with Numpy
• Analyzing Tabular Data with Pandas
• Visualization with Matplotlib and Seaborn
• Exploratory Data Analysis - A Case Study

💻 Code References

⭐️ Course Contents ⭐️
0:00:00 Course Introduction

Lecture 1
0:01:42 Python Programming Fundamentals
0:02:40 Course Curriculum
0:05:24 Notebook - First Steps with Python and Jupyter
0:08:30 Performing Arithmetic Operations with Python
0:11:34 Solving Multi-step problems using variables
0:20:17 Combining conditions with Logical operators
0:22:22 Adding text using Markdown
0:23:50 Saving and Uploading to Jovian
0:26:38 Variables and Datatypes in Python
0:31:28 Built-in Data types in Python
1:07:19 Further Reading

Lecture 2
1:08:46 Branching Loops and Functions
1:09:02 Notebook - Branching using conditional statements and loops in Python
1:09:24 Branching with if, else, elif
1:15:25 Non Boolean conditions
1:19:00 Iteration with while loops
1:28:57 Iteration with for loops
1:36:27 Functions and scope in Python
1:36:53 Creating and using functions
1:42:24 Writing great functions in Python
1:45:38 Local variables and scope
2:08:19 Documentation functions using Docstrings
2:11:40 Exercise - Data Analysis for Vacation Planning

Lecture 3
2:17:17 Numercial Computing with Numpy
2:18:00 Notebook - Numerical Computing with Numpy
2:26:09 From Python Lists to Numpy Arrays
2:29:09 Operating on Numpy Arrays
2:34:33 Multidimensional Numpy Arrays
3:03:41 Array Indexing and Slicing
3:17:49 Exercises and Further Reading
3:20:50 Assignment 2 - Numpy Array Operations
3:29:16 100 Numpy Exercises
3:31:25 Reading from and Writing to Files using Python

Lecture 4
4:02:59 Analysing Tabular Data with Pandas
4:03:58 Notebook - Analyzing Tabular Data with Pandas
4:16:33 Retrieving Data from a Data Frame
4:32:00 Analyzing Data from Data Frames
4:36:27 Querying and Sorting Rows
5:01:45 Grouping and Aggregation
5:11:26 Merging Data from Multiple Sources
5:26:00 Basic Plotting with Pandas
5:38:27 Assignment 3 - Pandas Practice

Lecture 5
5:52:48 Visualization with Matplotlib and Seaborn
5:54:04 Notebook - Data Visualization with Matplotlib and Seaborn
6:06:43 Line Charts
6:11:27 Improving Default Styles with Seaborn
6:16:51 Scatter Plots
6:28:14 Histogram
6:38:47 Bar Chart
6:50:00 Heatmap
6:57:08 Displaying Images with Matplotlib
7:03:37 Plotting multiple charts in a grid
7:15:42 References and further reading
7:20:17 Course Project - Exploratory Data Analysis

Lecture 6
7:49:56 Exploratory Data Analysis - A Case Study
7:50:55 Notebook - Exploratory Data Analysis - A case Study
8:04:36 Data Preparation and Cleaning
8:19:37 Exploratory Analysis and Visualization
8:54:02 Asking and Answering Questions
9:22:57 Inferences and Conclusions
9:25:00 References and Future Work
9:29:41 Setting up and running Locally
9:34:21 Project Guidelines
9:45:00 Course Recap
9:48:01 What to do next?
9:49:10 Certificate of Accomplishment
9:50:11 What to do after this course?
9:52:16 Jovian Platform

✏️ This course is taught by Aakash N S, co-founder, and CEO of Jovian.

[minowmuncher]

This course is the sole reason that I am able to feed my children.

[nguyenvinh]

If you don't know programming, there will always be an Indian to teach it for you on Youtube!

[legitMeastro]

Indian knowledge is blessing to Humans😂. Love you guys from Somalia

[leequist]

Today 17th December 2021, I start my journey in Data Analytics with Python. I know this will change my life and I pray for the strength and all the encouragement I need. Thanks to Jovian for giving low lives like myself the opportunity to learn for free. I owe u one.

[anshrastogi]

This course covered my whole semester's syllabus of Data Analysis and Visualization in just 3-4 hours. Thank you sir.

[abioyeorimadegun]

It's 22nd of December 2022, I've learnt Excel, SQL and Tableau and now I'm at the stage where I need to learn Python for Data Analysis and apply it to build portfolio projects. I already took a short course that focuses on Numpy and Pandas before getting to this video but I'm starting over 🤓

I will finish this course before the year runs out, 2023 is for building my portfolio and getting a job. My goal is to get a Data Analyst job before the end of Q1 2023. I believe I'll come here to share testimony of how this course helped 🚀🚀🚀

[hukushmolambi]

Just began with Python and I'm loving the experience. The easiness of Python's syntax is a major advantage for novices in coding. Furthermore, the adaptability of Python in different fields is truly impressive.

[teneaallen]

One of the best python tutorials I've watched. Thanks for being so detailed yet concise with your explanations and examples.

[dodogussi]

I started seeing this buds for fun and ended working as a freelance programmer at 16 what a life

[mishka]

Now *THIS* is what I should 10 hours watching, not TV shows and social media stuff!

[satviksatvik]

Just finished the first lecture! A few months back I joined a course on udemy (which is still on hold and I prefer this course over that) and that guy made it so difficult to understand, giving vague and difficult examples to explain what tuples, dictionaries are. But bro, you made it so simple and easy to understand! Thanks to you. I really like this course.

[navidsolangi]

This course is really useful. I was doing EDA on a project using R language but python seems so easy to do the same job. Love python and sincere thanks to Mr. Aakash.

[Krishna..]

Your fluency at English speaking skills and correct explanation blows to my mind
Great follower from my heart 🙏
Thanks

[tigere]

@1:39:48 For clarification we refer to function variables as Parameters at the function definition and as Arguments at the function invocation (call).

[pultural]

this is EXACTLY what I need right now. I’m speechless, thank you so much!!

[NasreenKhan-rubv]

Is this course still worth watching in 2024 (after 3 years) ?

[BookOfMorman]

I swear, this channel has a python script spying on me because this video couldn't have come at a better time! Thank you!!

[melodyfong]

THANK YOU! Everything is so detailed, neatly organised & there's so many exercises too!

[vainbow]

Thank god it's not just about cluelessly feeding data into statistical models without knowing how they work and getting garbage results like most "data analysis" courses creating self-proclaimed data scientists that couldn't explain the math behind a simple linear regression. This actually seems like a solid EDA course, nice.

[divyasnarayan]

Its jz Marvellous ! What a lecture, what an effort in making the viewers understand every concept, greatest ever ! 🙏