Master Numpy Foundation and Practice Challenging Exercises

Master Numpy Foundation and Practice Challenging Exercises, available at $39.99, has an average rating of 4.65, with 110 lectures, 48 quizzes, based on 30 reviews, and has 7606 subscribers.

You will learn about 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 is ideal for individuals who are Students interested towards Data Science career path or Existing Software Programmers who want to shift to Data Science career or Data Analyst who want to learn Programming or Beginners of Data Science It is particularly useful for Students interested towards Data Science career path or Existing Software Programmers who want to shift to Data Science career or Data Analyst who want to learn Programming or Beginners of Data Science.

Enroll now: Master Numpy Foundation and Practice Challenging Exercises

Summary

Title: Master Numpy Foundation and Practice Challenging Exercises

Price: $39.99

Average Rating: 4.65

Number of Lectures: 110

Number of Quizzes: 48

Number of Published Lectures: 110

Number of Published Quizzes: 48

Number of Curriculum Items: 158

Number of Published Curriculum Objects: 158

Original Price: ₹1,999

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

Students interested towards Data Science career path
Existing Software Programmers who want to shift to Data Science career
Data Analyst who want to learn Programming
Beginners of Data Science

Target Audiences

Students interested towards Data Science career path
Existing Software Programmers who want to shift to Data Science career
Data Analyst who want to learn Programming
Beginners of Data Science

This course helps you to build the foundation to work with Data Science. This course is not just learning PYTHON basics, 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 EPGDM Business Analytics Course and also got top ranking achievements in multiple data science competitions. The instructor have more than 16 years of experience in the IT industry. 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.

Feedback

PLEASE SUPPORT THIS COURSE BY YOUR HONEST REVIEW

Course Curriculum

Chapter 1: Course Introduction

Lecture 1: Overview – Course Structure

Lecture 2: Overview – Course Flow

Lecture 3: Overview – Best Recommendations

Lecture 4: Code Organization

Lecture 5: Exercises Organization

Lecture 6: How much time needed to complete this course

Chapter 2: Environment Setup

Lecture 1: Environment Requirements Part 1

Lecture 2: Environment Requirements Part 2

Lecture 3: How do you like this course ?

Lecture 4: Course Review links of udemy

Lecture 5: Anaconda Installation

Lecture 6: Plotly Installation

Lecture 7: Change Jupyter Notebook Startup Folder

Lecture 8: Download Code

Lecture 9: Download Exercises

Chapter 3: Python Introduction

Lecture 1: Introduction to Python

Lecture 2: Scope of Jupyter Notebook

Chapter 4: Jupyter Notebook

Lecture 1: Jupyter Notebook Part 1

Lecture 2: Jupyter Notebook Part 2

Lecture 3: Jupyter Notebook Part 3

Lecture 4: Jupyter Notebook Part 4

Lecture 5: Jupyter Notebook Part 5

Lecture 6: Open Jupyter Notebook quickly

Chapter 5: Python Basics – Variables, Operators and IF statement

Lecture 1: Variables

Lecture 2: Operators Part 1

Lecture 3: Operators Part 2

Lecture 4: Exercises – Operators

Lecture 5: IF Statement

Lecture 6: Exercises – IF Statement

Chapter 6: Python Basics – Strings

Lecture 1: Strings Part 1

Lecture 2: Strings Part 2

Lecture 3: Exercises – Strings

Chapter 7: Python Basics – List, Loops and List Comprehension

Lecture 1: List Part 1

Lecture 2: List Part 2

Lecture 3: Exercises – List

Lecture 4: Loops Part 1

Lecture 5: Loops Part 2

Lecture 6: Exercises – Loops

Chapter 8: Python Basics – Dictionary, Set and Tuple

Lecture 1: Dictionary

Lecture 2: Exercises – Dictionary

Lecture 3: Set

Lecture 4: Exercises – Set

Lecture 5: Tuple

Lecture 6: Exercises – Tuple

Chapter 9: Python Basics – Functions

Lecture 1: Functions Part 1

Lecture 2: Functions Part 2

Lecture 3: Functions Part 3

Lecture 4: Exercises – Functions

Chapter 10: Numpy Introduction

Lecture 1: Numpy Introduction

Chapter 11: Numpy Array Creation

Lecture 1: Numpy Array Creation Part 1

Lecture 2: Numpy Array Creation Part 2

Lecture 3: Numpy Array Creation Exercises

Chapter 12: Numpy Indexing

Lecture 1: Numpy Indexing Basics

Lecture 2: Exercises – Numpy Indexing Basics

Lecture 3: Numpy Boolean Indexing

Lecture 4: Exercises – Numpy Boolean Indexing

Lecture 5: Numpy Indexing View vs Copy Part 1

Lecture 6: Numpy Indexing View vs Copy Part 2

Chapter 13: Numpy Arithmetic Operations

Lecture 1: Numpy Arithmetic Operations Part 1

Lecture 2: Numpy Arithmetic Operations Part 2

Lecture 3: Exercises – Numpy Arithmetic Operations

Chapter 14: Numpy Sorting and Joining

Lecture 1: Numpy Sorting Part 1

Lecture 2: Numpy Sorting Part 2

Lecture 3: Exercises – Numpy Sorting

Instructors

Baskar S
Data Scientist,

Rating Distribution

1 stars: 1 votes
2 stars: 1 votes
3 stars: 1 votes
4 stars: 7 votes
5 stars: 20 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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