Master Numpy Foundation and Practice Challenging Exercises

[mitsumi]

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 102 lectures (8h 14m) | Size: 3.64 GB

Learn how to use Numpy from fundamentals of 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

Requirements
Basic Computer Knowledge
No Python knowledge is required
No Data Science knowledge is required

Description
This course helps you to build the foundation to work with Data Science. This course is not just learning numpy and python basics, 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 at the end of this course.

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 inorder 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 answers. 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

Activities Time

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.

Who this course is for
Beginners of Data Science
Students or anyone interested towards Data Science career path
Existing Software Programmers who want to shift to Data Science career

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