# The ULTIMATE Curriculum in Data Science

### This tutorial is special one for all the enthusiastic readers as i present you the ULTIMATE curriculum in Data Science.

In this curriculum, i will write myself series of chapters in an interesting and simple way.

The main highlights of this curriculum is

- It can be useful for all persons, i have written some points and through which you should judge your
**caliber**and start learning the series accordingly. - Interactive visualizations, examples, some important links and references that will help to understand concepts clearly.
- Use of simplified words and if anyone of you have any issue, just write down in the comments and i will make sure to solve your issues.
- And the most interesting thing that it stand’s out from other teaching curriculum is that you will learn only thing that has practical application in Data Science and it will surely make you a Data Master.

First Let’s get some motivation.

Now as you have pumped up and had been ready to disrupt the world through the power of data, let’s get to some basics.

As of now this tutorial is not yet completed but i will try my best that to add new tutorials daily. So just be patient and come to the tutorial later.

After completing this i will add a follow up post on “** How to reflect you learning of data science to others**” and i highly recommend you to try out your new power of Data Science on some of the world real life problems that can only be solved by these awesome people called as

**Data Scientists**.

Some important points to consider before starting the journey

- First select your caliber and then start your learning process.
- This Curriculum is arranged in different sections and each sections have different chapters.
- The only thing that is stopping from you to become true Data Scientist is only you, so you have to make a habit to learn something everyday.
- Focus on understanding the structure rather then just mugging up the code.
- And sometimes you will find some interesting concepts, topics or references that you think it should be added then just ping me and i will see to it.

### Let the Journey Begin..

### Caliber

- If you are just beginning and have no prior experience then i highly recommend you from
**Section-1: Prelude.** - If you know the basics of maths and statistics then also it is advisable to brush up topics and start from
**Section-2: Mathematics in Data Science.** - If you want to learn basics of python programming then go to
**Section-4: All you need to know about Python programming.**(remember we are using python for our code and if you want to learn Data Science in other language such as r, then i will make a follow up post on that too). - If you are the person who just want to go to try hands on Data Science, you should start from
**Section-5: Data Science 101: Importing and cleaning data.** - If you know the concepts of Machine Learning, and have some real life experiences with it, then you should start from
**Section-9: All about Deep Learning.**

### 2. Mathematics in Data Science

### 3. The wisdom of Statistics

- Multivariate Calculus
- Predictive Statistics
- Descriptive Statistics
- Hypothesis Testing
- Insights generation
- Root cause analysis
- Driven analysis

### 4. All you need to know about Python programming

- Python Basics

### 5. Data Science 101: Importing and cleaning data

- Ethics in Data Science
- Data importing
- Data cleaning
- Verifying the integrity of data.

### 6: The power of Data manipulation

### 7. Getting the true picture of data: Data Visualization

### 8. Learn Machine Learning the smart way

### 9. All about Deep Learning

### 10. AI and its power

### 11. *How to reflect you learning of data science to others*

*How to reflect you learning of data science to others*

As this is one hell of a massive curriculum, i will update the chapters later on as it is still incomplete, but expect to receive one chapter in every day or two.

Till then just relax, motivate yourself as i promise you that you will understand all the concepts that is required to disrupt Data Science.

Hope you will support me and if you find it worth the read just give me some motivation by clapping the hands and showing your interest in this idea.

To get the latest updates, tips and anything you want or have issue just post in the comments.

#### Till then….

#### Happy coding :)

And Don’t forget to clap clap clap…