Master Numpy Foundation and Practice Challenging Exercises

Learn Numpy and Python and practice 80 exercises and 350 quiz questions

What you'll learn:

• Learn Python Basics for Data Science
• Learn Numpy
• 60 challenging exercises in Numpy along with hints and solution files with explanation text for strong practice
• 20 exercises in Python along with hints and solution files with explanation text for practice
• Extensive and challenging quiz along with explanation for answers for all 350 questions
• Understand Key Statistics concepts
• Learn elaborately on how to implement key statistics concepts in Numpy
• Understand Key Linear Algebra concepts
• How to use numpy to implement key linear algebra concepts

This course helps you to build the foundation to work with Data Science. This course is not just learning PYTHONbasics, and NUMPY, the popular data science foundation package in python, but also provides students and programmers to get practice with lot of challenging exercises while you learn. Thus, students get strong hands-on with numpy when they complete this course.

Instructor

The Instructor of this course is the university topper in EPGDMBusiness Analytics Course and also got top ranking achievements in multiple data science competitions. The instructor have more than 16 years of experience in the ITindustry. Please refer to the Udemy Instructor section for more detail.

Exercises

No of Exercises in Python: 20

No of Exercises in Numpy: 60+

These exercises are specially designed to get the hands on immediately after completion of every topic. The solution files contain not just the code alone, but also embedded with the detailed explanation of the solution. Additionally, hints files are provided for exercises in-order for students to avoid viewing the solution before completing the exercise.

Quiz

No of questions: 350

You might think that every course has got quiz, then what’s so special about quiz in this course.

This course contains specially designed quiz to have challenging questions with explanations for all choices. The questions include testing the output of the code, questions forces students to analyse all the choices etc.

Content

At high level, this course covers following chapters:

• Python Basics

• Numpy

• Statistics concepts

• Numpy for Statistics

• Linear Algebra Concepts

• Numpy for Linear Algebra

Practice Effort

Besides lecture duration, students will spend valuable 60 hours for exercises and quiz questions. You can see the detail of this time in preview videos.

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