Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
8 Hour(s) 28 Minute(s)
Language
English
Taught by
Baskar S
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
2 views
Course Overview
Learn Numpy, Python, Statistics and Linear Algebra and practice 80 exercises and 350 quiz questions
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 Content
- 24 section(s)
- 110 lecture(s)
- Section 1 Course Introduction
- Section 2 Environment Setup
- Section 3 Python Introduction
- Section 4 Jupyter Notebook
- Section 5 Python Basics - Variables, Operators and IF statement
- Section 6 Python Basics - Strings
- Section 7 Python Basics – List, Loops and List Comprehension
- Section 8 Python Basics – Dictionary, Set and Tuple
- Section 9 Python Basics - Functions
- Section 10 Numpy Introduction
- Section 11 Numpy Array Creation
- Section 12 Numpy Indexing
- Section 13 Numpy Arithmetic Operations
- Section 14 Numpy Sorting and Joining
- Section 15 Statistics Introduction
- Section 16 Statistics - Central Tendency
- Section 17 Numpy for Statistics – Central Tendency and Simple statistics
- Section 18 Statistics - Spread
- Section 19 Numpy for Statistics – Spread
- Section 20 Statistics - Outlier
- Section 21 Numpy for Statistics – Outlier
- Section 22 Linear Algebra
- Section 23 Numpy for Linear Algebra
- Section 24 Bonus
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
Reviews
-
MMed
bien expliquer. merci pour votre effort
-
LLuis Cortazar
Great teaching course abot Numpy
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WWilfredo Aguilar
Great course for those who would like to know more of Numpy.
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MMohanbabu
Good one..👍
