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Ultimate Python Bootcamp For Data Science & Machine Learning

Learn How To Code Python For Data Science, ML & Data Analysis, With 100+ Exercises and 4 Real Life Projects !

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Last updated 12/2023
English

Overview

Hi, Dear learning aspirants welcome to "Ultimate Python Bootcamp For Data Science & Machine Learning" from beginner to advanced level. We love programming. Python is one of the most popular programming languages in today’s technical world. Python offers both object-oriented and structural programming features. Hence, we are interested in data analysis with Pandas in this course. 

This course is for those who are ready to take their data analysis skill to the next higher level with the Python data analysis toolkit, i.e. "Pandas".

This tutorial is designed for beginners and intermediates but that doesn't mean that we will not talk about the advanced stuff as well. Our approach of teaching in this tutorial is simple and straightforward, no complications are included to make you bored Or lose concentration. 

In this tutorial, I will be covering all the basic things you'll need to know about the 'Pandas' to become a data analyst or data scientist.   

We are adopting a hands-on approach to learn things easily and comfortably. You will enjoy learning as well as the exercises to practice along with the real-life projects (The projects included are the part of large size research-oriented industry projects).

I think it is a wonderful platform and I got a wonderful opportunity to share and gain my technical knowledge with the learning aspirants and data science enthusiasts.

Who this course is for

  1. Beginner Python developers - Curious to learn about Data Science Or Data Analysis
  2. Data Analysis Beginners
  3. Aspiring data scientists who want to add Python to their tool arsenal
  4. Students and Other Professionals
  5. AI and ML aspirants to upgrade their knowledge in Data Pre-processing before applying the machine learning algorithms to their projects
  6. Data Analyst job seekers who wants to update their Resume with Python's data analysis toolkit

Testimonials

  1. I have recently completed a course on python for data analysis with pandas. I am a mechanical engineer but wanted to do career in data science. And this course was simply great. Thank you for an awesome course from basic to advanced ~ Sagar K
  2. Thank you so much for this course by Mentor Mr.Prithiviraja L . Kudos to you. I was learning pandas for past 6 months, but I couldn't able to remember syntax for some basics. But, I continously watched your videos for past 10 days and completed the course. Within 10 days, I am ready to do data analysis with pandas. Thank You Sir for your great effort. I'll surely recommend your course to someone who wants to learn data analysis with pandas ~ Kamalakannan
  3. Extremely Very beneficial course for freshers and beginners in Data Science and Machine Learning ~ A Mahato
  4. This Course was very good. It is very useful for those who are entering for the training on Data Science Courses ~ Rodda A

What you'll learn

You will become a specialist in the following things while learning via this course:

“Data Analysis With Pandas”

  1. You will be able to analyze a large file
  2. Build a Solid Foundation in Data Analysis with Python

After completing the course you will have professional experience on:

  1. Pandas Data Structures: Series, DataFrame and Index Objects
  2. Essential Functionalities
  3. Data Handling
  4. Data Pre-processing
  5. Data Wrangling
  6. Data Grouping
  7. Data Aggregation
  8. Pivoting
  9. Working With Hierarchical Indexing
  10. Converting Data Types
  11. Time Series Analysis
  12. Advanced Pandas Features and much more with hands-on exercises and practice works

Requirements

  1. Students must be willing to learn the Data Analysis with Python language
  2. If you know basics of Python that is well and good
  3. Basic Or intermediate experience with Microsoft Excel or another spreadsheet software, but not necessary
  4. Basic knowledge of data types (strings, integers, floating points, Booleans) etc, but not necessary
  5. Basic Programming knowledge Or knowing any other programming languages will also helps
Show all

Course Content

11 Sections 102 Lectures 15h 41m total length

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