Python Programming for Beginners in Data Science

Python Programming for Beginners in Data Science, available at $74.99, has an average rating of 4.23, with 105 lectures, 24 quizzes, based on 3224 reviews, and has 122396 subscribers.

You will learn about Learn just enough Python Programming to do Data Science, Machine Learning and Deep Learning Have a good understanding of the core concepts of Python Programming Form a good programming base to be able to apply it to Machine Learning Algorithms Just enough Object Oriented Python as well This course is ideal for individuals who are Non-Programmers interested to learn Python as their first language or Non-Python Programmers interested in learning Python for Machine Learning and Data Science It is particularly useful for Non-Programmers interested to learn Python as their first language or Non-Python Programmers interested in learning Python for Machine Learning and Data Science.

Enroll now: Python Programming for Beginners in Data Science

Summary

Title: Python Programming for Beginners in Data Science

Price: $74.99

Average Rating: 4.23

Number of Lectures: 105

Number of Quizzes: 24

Number of Published Lectures: 105

Number of Published Quizzes: 23

Number of Curriculum Items: 129

Number of Published Curriculum Objects: 128

Original Price: $39.99

Quality Status: approved

Status: Live

What You Will Learn

Learn just enough Python Programming to do Data Science, Machine Learning and Deep Learning
Have a good understanding of the core concepts of Python Programming
Form a good programming base to be able to apply it to Machine Learning Algorithms
Just enough Object Oriented Python as well

Who Should Attend

Non-Programmers interested to learn Python as their first language
Non-Python Programmers interested in learning Python for Machine Learning and Data Science

Target Audiences

Non-Programmers interested to learn Python as their first language
Non-Python Programmers interested in learning Python for Machine Learning and Data Science

Data Science, Machine Learning, Deep Learning & AI are hot areas right now. But to learn these, for some of us programming is a bit of a problem. Not all of us are from a programming background. Or some come from a Java background and might not know Python.

These days, Python is the de-facto ( almost ) programming language for Data Science. So, to fill that gap, we have created a course that covers just enough Python for you to start up and running with any of you the Machine learning algorithms you are interested in.

Python Programming–

Python programming is one of the core skills required for any Data Scientist. However, not all wanna-be data scientists have the required programming background let alone Python skills. This Python online training program is designed to let you start all the way from the basics. It teaches you the basic skills in python. Here are some of the topics we will discuss in the course. You don’t have to understand these topics just yet. The listing is to just give a good inventory of the topics that we will be covering in this Python course.

variables, type conversions, flow control, operators & Expressions.
Loops – for & while loops , nested loops, for else loops
Strings, built-in and user defined functions
Data Structures – Lists, Dictionaries, Tuples, Sets
Object Oriented Python
I/O, exceptions
Standard library – date/time, file I/O, math, statistics & random numbers.

For any data scientist, these are the absolute essentials of python.

What about Data Science & Machine Learning ?

This course does NOT teach you data science or machine learning. Python is a broad purpose programming langauge. It can be used for a variety of purposes like building websites, process automation, devops, Data science etc. However, this Python programming course is designed specifically to cater to the needs of the Machine Learning or Data Science learner. By the end of this course, you will be in a good position to apply your python skills to apply to any of the Machine Learning or Data Science algorithms in Python.

Who this course is not for ?

Although most newbies or experienced folks will benefit from this course, it is not suitable for

those experienced in Python already.
those who already have some Python programming experience, but wish to learn more about its application in Data Science or Machine learning.

Free Preview

We have deliberately kept quite a number of videos for free preview. Hopefully, this will enable you to judge our Python Programming course before you take it. Either way, Udemy’s 30 day return program will hopefully help you with a refund in case you don’t like the course. However, we are absolutely positive you will like the course.

Course Curriculum

Chapter 1: Day 0 – Python Setup

Lecture 1: Why Python

Lecture 2: About the Course

Lecture 3: Python Setup

Lecture 4: Hello World in Python

Lecture 5: Python IDE Setup

Chapter 2: Day 1 – Python Basics

Lecture 1: What are Variables

Lecture 2: Variables – Types of Numbers

Lecture 3: Variables – Strings, Boolean & Reserved Keywords

Lecture 4: Variables – Quiz

Lecture 5: Variables – Recap

Lecture 6: Variables – Challenge – Discussion

Lecture 7: Type Conversion

Lecture 8: Type Conversion Quiz Discussion

Lecture 9: Arithmetic Operators

Lecture 10: Comparision Operators

Lecture 11: Operator Precedence

Lecture 12: Logical Operators

Chapter 3: Day 1 (contd) – Flow Control

Lecture 1: if statement

Lecture 2: python blocks

Lecture 3: nested if statement

Lecture 4: elif statement

Lecture 5: else statement

Lecture 6: flow control quiz – discussion

Lecture 7: flow control challenges – discussion

Chapter 4: Day 2 – Loops

Lecture 1: for loop

Lecture 2: While loop

Lecture 3: Challenge Discussion – 1

Lecture 4: Challenge Discussion – 2

Lecture 5: Challenge Discussion – 3

Lecture 6: for vs while loop

Lecture 7: Break Statement – Theory

Lecture 8: Break Statement – Program

Lecture 9: for-else statement

Lecture 10: Nested loops

Chapter 5: Day 3 – Strings & Functions

Lecture 1: What are Strings

Lecture 2: Sub-strings

Lecture 3: Split strings

Lecture 4: Strip strings

Lecture 5: Other String Functions

Lecture 6: Cheatsheet

Lecture 7: Challenges

Lecture 8: Python Functions

Lecture 9: Create your own Function

Lecture 10: doc string

Lecture 11: function arguments

Lecture 12: Python functions – Summary

Lecture 13: Python Built-in Functions

Lecture 14: Python Built-in functions Summary

Chapter 6: Day 4 – Data Structures – Lists

Lecture 1: What are Lists

Lecture 2: Challenge

Lecture 3: List Indexing and Merging

Lecture 4: List Manipulation

Lecture 5: Challenge – Average Grades v3

Lecture 6: Challenge contd.

Lecture 7: Challenge contd.

Lecture 8: Nested Lists

Lecture 9: Enumerate Lists

Lecture 10: Merge and Sort Lists

Lecture 11: List Slicing

Lecture 12: Python Dictionary

Lecture 13: get-vs-index

Lecture 14: Challenge – Vowels

Lecture 15: Dictionary access

Lecture 16: Dictionary – Key & Value objects

Lecture 17: Challenge – 1

Lecture 18: Challenge – 2

Lecture 19: Challenge – 2 ( contd)

Lecture 20: Dictionary – Deletion

Chapter 7: Day 5 – Data Structures (contd.)

Lecture 1: Python Tuples

Lecture 2: Python Tuples ( contd. )

Lecture 3: Python Sets

Instructors

Ajay Tech
IT Courses Data Science, Machine Learning, React, Full Stack

Rating Distribution

1 stars: 44 votes
2 stars: 77 votes
3 stars: 480 votes
4 stars: 1262 votes
5 stars: 1361 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?

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