Introduction to Python

Power up your career with the best and most popular data science language, Python. Leverage your Python skills to start your Data Science journey. This course is intended for beginners with no coding or Data Science background.

Learn Python for Data Science

Do you want to enter the field of Data Science? Are you intimidated by the coding you would need to learn? Are you looking to learn Python to switch to a data science career?

You have come to just the right place!

Most industry experts recommend starting your Data Science journey with Python
Across biggest companies and startups, Python is the most used language for Data Science and Machine Learning Projects
Stackoverflow survey for 2019 had Python outrank Java in the list of most loved languages

Python is a very versatile language since it has a wide array of functionalities already available. The sheer range of functionalities might sound too exhaustive and complicated, you don’t need to be well-versed with them all.

Most data scientists have a few go-to libraries for their daily tasks like:

for performing data cleaning and analysis - pandas
for basic statistical tools – numpy, scipy
for data visualization – matplotlib, seaborn

Why Python and how popular is it for Data Science?

Python has rapidly become the go-to language in the data science space and is among the first things recruiters search for in a data scientist's skill set.
It consistently ranks top in global data science surveys and its widespread popularity will only keep on increasing in the coming years.
Over the years, with strong community support, this language has obtained a dedicated library for data analysis and predictive modelling.

This python data science course will help you learn Python libraries like Pandas and use them efficiently for data science and data analysis. Are you ready to power up your career and learn the best data science language?

This course will help you learn Python libraries like Pandas and use them efficiently for data science and data analysis.
Are you ready to power up your career and learn the best data science language?

Enroll now

What does a Data Scientist do?

Data Science is an amalgamation of Statistics, Computer Science and specific domain knowledge.
As more and more data gets generated across the world, we need to leverage it to make decisions and improve them.
A data scientist performs operations on the data provided to analyze and interpret it.

Which companies use Python?

Many of the biggest and most popular companies use Python. Some of them are:

Google, NASA, Amazon
Social networking sites like Instagram, Reddit, Quora, etc
Media streaming companies like Netflix and Spotify
Rideshare companies like Uber and Lyft

“Python has been an important part of Google since the beginning and remains so as the system grows and evolves. Today dozens of Google engineers use Python, and we are looking for more people with skills in this language.”

- Peter Norvig, Director of Research at Google Inc.

So get onboard the Data Science train by learning Python and upskill yourself with one of the Top Data Science Courses offered by Analytics Vidhya!

What do I need to start with Python for Data Science course?

A working laptop / desktop with 4 GB RAM
A working Internet connection

A Python Data Science Course is all it takes for you to learn one of the popular language in Data Science.
What are you waiting for?

Enroll for Free Now

What do I need to start with Python for Data Science course?

Course curriculum for Python for Data Science

1

Overview of the Course
- Overview of the Course
- AI&ML Blackbelt Plus Program (Sponsored)
2

Introduction to Python
- A brief introduction to Python
- Introduction to Python Test
- Installing Python
- Become a BlackBelt in Data Science
3

Understanding Operators
- Theory of Operators
- Exercise
- Understanding Operators in Python
- Operators Test
4

Variables and Data Types
- Understanding variables and data types
- Variable Test
- Variables and Data Types in Python
- Exercise
5

Conditional Statements
- Understanding Conditional Statements
- Exercise
- Implementing Conditional Statements in Python
- Conditional Statements test
6

Looping Constructs
- Understanding Looping Constructs
- Exercise
- Implementing Looping Constructs in Python
- Looping Constructs test
7

Functions
- Understanding Functions
- Implementing Functions in Python
- Functions test
8

Data Structure
- A brief introduction to data structure
- Data Structure test
9

Lists
- Understanding the concept of Lists
- Lists test
- Implementing Lists in Python
- Exercise
10

Dictionaries
- Understanding the concept of Dictionaries
- Exercise
- Implementing Dictionaries in Python
- Dictionaries test
11

Understanding Standard Libraries in Python
- Understanding the concept of Standard Libraries
- Libraries test
12

Reading a CSV File in Python
- Reading a CSV File in Python - Introduction to Pandas
- Reading a CSV file in Python: Implementation
- Reading a csv file in Python test
13

Data Frames and basic operations with Data Frames
- Understanding dataframes and basic operations
- DataFrames and basic operations test
- Reading dataframes and conduct basic operations in Python
- Reading dataframes and conduct basic operations in Python Test
14

Indexing a Data Frame
- Indexing a Dataframe
- Indexing DataFrames test
- Exercise
15

Data Manipulation and Visualization
- Sorting Dataframes
- Merging Dataframes
- Quiz: Sorting and Merging dataframes
- Apply function
- Aggregating data
- Quiz: Apply function and Aggregating data
- Basics of Matplotlib
- Data Visualization using Matplotlib
- Quiz: Matplotlib
- Basics of Seaborn
- Data Visualization using Seaborn
- Quiz: Seaborn
16

Regular Expressions
- Understanding Regular Expressions
- Quiz: Regular Expressions
- Regular Expressions in Python
- Quiz: Regular Expressions in Python
17

Cheatsheet for Python
- Cheatsheet for Python
18

Evaluate
- Instructions
- Quiz
- Python Coding Challenge
- Test your Skills: Python
19

Feedback
- Poll
20

Where to go from here?
- Where to go from here?

Certificate of Completion

Upon successful completion of the course, you will be provided a block chain enabled certificate by Analytics Vidhya with lifetime validity.

Common Questions Beginner ask about Python for Data Science Courses?

Do I need to learn coding to learn Python?

If you are totally new to programming, no need to get intimidated by learning a whole new language.

Python is a very easy language to learn:

It does not have a complicated syntax and understanding Python is very intuitive.
You don’t need to be skilled in coding for getting started in Python.

This course is for beginners we will start right from the foundations to performing data analysis tasks in Python.

I am familiar with other Programming Languages like Java/C++. Will this course help me to migrate to Python?

Do you know that Python is essentially a wrapper on C? That is what makes it fast and easy to understand!

Though Python has recently become popular amongst Data Scientists, it was originally a general-purpose language.
Python is still object-oriented and follows many of the paradigms that Java does.
So if you are familiar with the concepts of programming, you can migrate to Python easily with this course.

How much Python do I need to know to enter Data Science?

Though Python has hundreds of libraries and many more functionalities, you don’t need to know all of them for learning Data Science
Rather than becoming an expert in the entire language, you would need to just be acquainted with the basic syntax of Python.
We will also cover the most popular libraries used by Data Scientists and which you would be using too as a future Data Scientist!

What if I don’t have Python installed on my system?

One of the best things about Python is the wide variety of platform that support writing it.

We will provide easy to follow instructions to work with Python using Anaconda, an extremely popular package manager platform. No matter what Operating System you are using, we have you covered with guides for all of them.

What are the most popular open-source libraries that Python supports?

pandas, numpy, scipy, matlplotlib, seaborn are used for Data Science and Data Analysis
scikit-learn, tensorflow, keras are used for basic and advanced machine learning
libraries for deep learning like OpenCV(Computer Vision), NLTK(Natural Language Processing)

Will I be able to apply what I have learnt here to machine learning and data science projects?

The Python for Data Science course is designed to help you completely understand Python and start using it immediately for Data Science projects.
With regular assignments, quizzes and hands-on projects, you will be full equipped with the essential data science skillsets.

Frequently Asked Question

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