Complete guide to begin with Python for Data Science
What you'll learn
- Learn how to use Jupyter Notebook efficiently for Programming
- Learn fundamentals of Python Programming Language and how to approach Python Assignments and solve them
- Learn various data structures of Python - List, set, tuple, dictionaries
- Learn how developers use Exception Handling for handling errors.
- Learn how to use if else statements, loops with certain illustrations
- Learn how to use functions and recursion to build a python project
- Learn advanced functions - map and lambda which will be used in data science frequently
- Get ready to appear for any interview, assignment, projects related to data science, development
- Learn Variables and data types in detail.
- Learn how to format strings and print statements
Requirements
- Simple Mathematics - Addition, Subtraction, Multiplication, Division
Description
A complete guide to begin your python learning for data science, data analysis and machine learning.
For those, who has never written a single code in entire life and want to move into data science or advanced python, this course provides you a simple approach to learn coding from scratch using python as a tool and master it with illustrations and assignments.
For those, who are already experienced in coding, but want to move into advanced python, this course provides you ample hands-on exercises and assignments for deeply understanding the concept.
In this course, you will be learning from the very basics - which includes basic numbers, arithmetic operations, lists, sets, tuples, dictionaries, loops, if else statements, nested dictionaries, functions, recursive functions etc.
We will be using Jupyter notebook in order to execute all the codes. Jupyter notebook is a tool that is being used by all the multinational organisation, who hire people for analytics and machine learning jobs.
Key features:
# Learn Python from scratch - from installation to writing your first code to understand the basics and finally to reach advance level.
# No prior coding experience required.
# Command yourself in Jupyter Notebook.
# Prepare yourself for Data Analytics, Machine Learning, Python Development.
Have a great learning ahead.
Who this course is for:
- Beginner Python developers
- Data science aspirants
- web development aspirants
- Python for interview preparation
- Data Analytics aspirants
Instructor
![Play With Data](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.7 Instructor Rating
- 4 Reviews
- 10 Students
- 1 Course
Hi there, I'm Harshit..
From beginning, I was extensively interested in Problem Solving.
I started coding from first job. I was scared in the beginning because I had never written a single code before.
But soon I realized that its not about the code or syntax, its about the algorithm you use.
If you know how to solve that problem, than you just need to find the resources to solve that problem.
Since then, I always considered coding assignment or project as a problem statement and C, C++, Python or any programming language as a tool to get the solution.
Now I am working as a data scientist where I work on multiple Python libraries like Numpy, Pandas, Seaborn, Matplotlib, Beautiful soup, NLTK, Scikit Learn.
I also have an experience in R programming, Tableau.
Now, as I have mentioned too many libraries, but each library has its own functionality - Pandas for data analytics, beautiful soup for we scraping, NLTK for text mining, Seaborn for Visualization etc, so it depends on a project which library you will be using.
Soon I will be releasing courses for all above libraries and tools.
I am building this course to get individuals like me comfortable with all above tools, so that if we get a chance to work on them or to answer any question or to do any assignment or project, we shouldn't be having any concern or suspicion.
Thank you...
Take care...