Python and Analytics for Data Science
Kick Start Your Data Science Career from Beginner to Master
Lectures -48
Resources -40
Duration -8.5 hours
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Course Description
This course is meant for beginners and intermediates who wants to expert on Python programming concepts and Data Science libraries for analysis, machine Learning models etc.
They can be students, professionals, Data Scientist, Business Analyst, Data Engineer, Machine Learning Engineer, Project Manager, Leads, business reports etc.
The course have been divided into 6 parts - Chapters, Quizzes, Classroom Hands-on Exercises, Homework Hands-on Exercises, Case Studies and Projects.
Practice and Hands-on concepts through Classroom, Homework Assignments, Case Studies and Projects
This Course is ideal for anyone who is starting their Data Science Journey and building ML models and Analytics in future.
This course covers all the important Python Fundamentals and Data Science Concepts requires to succeed in Academics and Corporate Industry.
Opportunity to Apply Data Science Concepts in 3 Real World Case Studies and 2 Real World Projects.
The 3 Case Studies are on Loan Risk Analysis, Churn Prediction and Customer Segmentation.
The 2 Projects are on Titanic Dataset and NYC Taxi Trip Duration.
The recommended approach for this course - Follow the chapters in their order, Do Yourself all the Hands-on Exercises. Finally, Consistency, discipline and practice is paramount.
This course will not teach you how to build and develop ML models. But, make you expert at python programming language which is needed to build ML models.
Goals
Become an Expert at Python fundamentals and Data Science Packages such as Pandas, Numpy, and Visualization
This course is ideal for anyone to start their Data Science Journey
Practice and Hands-on concepts through Quizzes, Classroom, Homework Assignments, Case Studies, and Projects
Opportunity to Apply Data Science Concepts into 3 Real World Case Studies and 2 Real World Projects
This course covers all the important Python Fundamentals and Data Science Concepts requires to succeed in Academics and Corporate Industry
Prerequisites
- There is no technical or prior programming knowledge is required. Â This course only requires your commitment and practice to become expert at Python.
- It requires your local desktop/Laptop (Windows or Mac) or Google Account (Optional)
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Curriculum
Check out the detailed breakdown of what’s inside the course
Course Introduction and Structure
2 Lectures
-
Introduction 08:05 08:05
-
Course Materials
Python Installation
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Introduction to Variables and Strings
7 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
List, Tuple and Dictionary
5 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Conditions and Loops
5 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Functions and Case Study 1
4 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Data Science: Numpy and Functions
5 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Data Science: Pandas Package and Case Study 2
9 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Data Science: Data Visualization
5 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Case Study 3 and Projects
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Instructor Details
![Mohit Jain](https://www.tutorialspoint.com/assets/profiles/555487/profile/200_1247486-1669832974.jpg)
Mohit Jain
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