Data Science


Python-Introduction to Data Science and Machine learning A-Z

Python basics Learn Python for Data Science Python For Machine learning and Python Tips and tricks

4.18 (1097 reviews)

Python-Introduction to Data Science and Machine learning A-Z



7.5 hours


Sep 2020

Last Update
Regular Price

What you will learn

Uderstand the basics of python programming

learning all the basic mathematical concepts

Understand the basics of Data science and how to perform it using Python

Learn to use different python tools specialisez for data science

Improve your python programming by integrating new concepts

Learning the basics of Machine learning

Perform various analysis with sklearn

Finish the course with a complete understand of all the core concepts of Data science and all the required tools to perform it with python


Learning how to program in Python is not always easy especially if you want to use it for Data science. Indeed, there are many of different tools that have to be learned to be able to properly use Python for Data science and machine learning and each of those tools is not always easy to learn. But, this course will give all the basics you need no matter for what objective you want to use it so if you :

- Are a student and want to improve your programming skills and want to learn new utilities on how to use Python

- Need to learn basics of Data science

- Have to understand basic Data science tools to improve your career

- Simply acquire the skills for personal use

Then you will definitely love this course. Not only you will learn all the tools that are used for Data science but you will also improve your Python knowledge and learn to use those tools to be able to visualize your projects.

The structure of the course

This course is structured in a way that you will be able to to learn each tool separately and practice by programming in python directly with the use of those tools. Indeed, you will at first learn all the mathematics that are associated with Data science. This means that you will have a complete introduction to the majority of important statistical formulas and functions that exist. You will also learn how to set up and use Jupyter as well as Pycharm to write your Python code. After, you are going to learn different Python libraries that exist and how to use them properly. Here you will learn tools such as NumPy or SciPy and many others. Finally, you will have an introduction to machine learning and learn how a machine learning algorithm works. All this in just one course.

Another very interesting thing about this course it contains a lot of practice. Indeed, I build all my course on a concept of learning by practice. In other words, this course contains a lot of practice this way you will be able to be sure that you completely understand each concept by writing the code yourself.

For who is this course designed

This course is designed for beginner that are interested to have a basic understand of what exactly Data science is and be able to perform it with python programming language. Since this is an introduction to Data science, you don't have to be a specialist to understand the course. Of course having some basic prior python knowledge could be good but it's not mandatory to be able to understand this course. Also, if you are a student and wish to learn more about Data science or you simply want to improve your python programming skills by learning new tools you will definitely enjoy this course. Finally, this course is for any body that is interested to learn more about Data science and how to properly use python to be able to analyze data with different tools.

Why should I take this course

If you want to learn all the basics of Data science and Python this course has all you need. Not only you will have a complete introduction to Data science but you will also be able to practice python programming in the same course. Indeed, this course is created to help you learn new skills as well as improving your current programming skills.

There is no risk involved in taking this course

This course comes with a 100% satisfaction guarantee, this means that if your are not happy with what you have learned, you have 30 days ​to get a complete refund with no questions asked. Also, if there is any concept that you find complicated or you are just not able to understand, you can directly contact me and it will be my pleasure to support you in your learning.

This means that you can either learn amazing skills that can be very useful in your professional or everyday life or you can simply try the course and if you don't like it for any reason ask for a refund.

You can't lose with this type of offer !!

ENROLL NOW and start learning today :)




What is Data Science

Installation of Anaconda and Jupyter

Introduction to Jupyter Part 1

Introduction to Jupyter Part 2

Basic Statstics knowledge

The Basics of Data

The basics of statistics part 1

The basics of statistics part 2

The basics of statistics part 3

The basics of statistics part 4

The basics of statistics part 5

The basics of statistics part 6

Python library: NumPy

Introduction to Numpy

Setting up NumPy

Basic calculations Part 1

Basic calculations Part 2

Basic calculations Part 3

Basic calculations Part 4

Basic calculations Part 5

Python library: Pandas

The Basics of Pandas

Setting up Pandas

Pandas operations part 1

Pandas operations part 2

Pandas operations part 3

Pandas operations part 4

Pandas operations part 5

Python library: Scipy

The Basics of SciPy

SciPy operations part 1

SciPy operations part 2

SciPy operations part 3

SciPy operations part 4

SciPy operations part 5

Python library : Matplotlib

Introduction to Matplotlib

Setting up MatPlotlib

Basics of matplotlib part 1

Basics of matplotlib part 2

Basics of matplotlib part 3

Basics of matplotlib part 4

Basics of matplotlib part 5

Python library: Seaborn

Introduction to Seaborn

Setting up seaborn

Seaborn operations part 1

Seaborn operations part 2

Seaborn operations part 3

Seaborn operations part 4

Machine Learning

Introduction to machine learning

Presentation of Different algorithms

Machine learning algorithms part 1

Machine learning algorithms part 2

Machine learning algorithms part 3




Ben20 October 2020

*** A click-bate use of buzzwords *** If you've heard of death by power-point then brace yourself because this is worse. Sorry. This is awful. I understand the droll subject and the primitive ideal given it's an introduction; however, all this course consists of is 10+ minutes segments of staring at one slide with one or two sentences or a picture with no context while the 'lecturer' rabbits on about arbitrary nonsense to pass the time. How many times can one person say Data Science per slide... That's rhetorical. Although, indicative to the relative nature of how Data Science is represented in this 'lecture'. Simply saying the words Data Science doesn't constitute the application of use. This may be an "introduction" however this doesn't give reason to simply waste people's time. Please let me save yours' and suggest a more productive use of time by Googling 'What is Data Science? This, whatever you want to call, is approx six hours of rambling garbage and a perfect example of where a title for a course is all a curator cared to put effort into...

Om17 October 2020

It is very much introductory course. If you will go for another data science course you can learn much more things.

Abhishek12 October 2020

the course is really good for beginners, easy to understand the basic concepts of data science and machine learning but need little elaboration with examples

Amit10 October 2020

It's good so far as i am getting the basics theoretical concepts of Data science, would prefer the live demo later....

Shamim7 October 2020

It was great so far :-) Thank you. Everything is explained clearly from the beginning, which made me feel relieved and comfortable.

Sebastian4 October 2020

More explanations and insights instead of just saying "it's pretty simple" would be nice. Sometimes it is more a rushing through function calls. Summed up, it's good to get an overview. Not more, not less.

Anthony4 October 2020

Talking a lot but not really saying anything, things like simple spelling errors in slides make it look more effort could have been put into the presentations

Rajib2 October 2020

This course is amazing i really really like this course.l am very happy to get this course. ? Thank you very much sir and udemy?

Victor28 September 2020

Many of the concepts here explained are incorrect, basic things like what's a column and what's a row were wrong which is a bad sign. The examples are not intuitive. Slides are prettier than useful/helpful. A course like this is supposed to build strong foundations on the subject but this course is just lame and can be misleading sometimes. I couldn't finish it, the deeper I went the worst it got.

JayPrakash28 September 2020

loved it as a beginner student for Data science and the way u let people understand its very great and thankyou for ur course

Visudha24 September 2020

That's the exact course I'm longing for few years ago.Lecturer's clear and tidy explaination make me so energetic powered driven to continue learning and really pleased to meet this expert lecturer and I want to say " Hello teacher and thank you very very much. Visudha Cara[Tin Htun] fron - Myanmar.

Jaime14 September 2020

Este curso me está ayudando adquirir nuevos conocimientos en el ámbito de la programación para conocer nueva metodología que se puede aplicar en el campo de la informática.

Joydeep13 September 2020

The introduction video was a little long but nevertheless I enjoyed it Thank You for your hard-work and your time.

Bijesh5 September 2020

It's very helpful to understand the basic of Data Science, hope it'll be improve over time and meet with latest trend in data science.

Adam4 September 2020

Good tutor. But for the love of god make the text (in python while showing practical) bigger! Also...you kind of rushed through lesson .50 - there's much there that hadn't been covered before


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Lee Jia Cheng
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