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Development Data Science Python

Python A-Z™: Python For Data Science With Real Exercises!

Programming In Python For Data Analytics And Data Science. Learn Statistical Analysis, Data Mining And Visualization
Rating: 4.6 out of 54.6 (19,572 ratings)
124,342 students
Created by Kirill Eremenko, Ligency Team
Last updated 3/2021
English
English, Portuguese [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Learn to program in Python at a good level
  • Learn how to code in Jupiter Notebooks
  • Learn the core principles of programming
  • Learn how to create variables
  • Learn about integer, float, logical, string and other types in Python
  • Learn how to create a while() loop and a for() loop in Python
  • Learn how to install packages in Python
  • Understand the Law of Large Numbers
Curated for the Udemy for Business collection

Course content

8 sections • 75 lectures • 11h 10m total length

  • Preview08:55
  • BONUS: Learning Paths
    00:34
  • Get the materials
    00:05
  • Some Additional Resources!!
    00:13
  • FAQBot!
    01:29
  • Your Shortcut To Becoming A Better Data Scientist!
    02:05

  • Updates on Udemy Reviews
    01:09
  • Types of variables
    08:44
  • Using Variables
    08:58
  • Boolean Variables and Operators
    06:03
  • The "While" Loop
    09:56
  • The "For" Loop
    07:57
  • Preview12:29
  • Code indentation in Python
    02:40
  • Section recap
    03:08
  • HOMEWORK: Law of Large Numbers
    12:51
  • Core Programming Principles
    5 questions

  • What is a List?
    03:15
  • Let's create some lists
    08:42
  • Using the [] brackets
    06:28
  • Slicing
    09:27
  • Tuples in Python
    06:17
  • Functions in Python
    05:37
  • Preview13:39
  • Numpy and Arrays in Python
    07:08
  • Slicing Arrays
    04:32
  • Section Recap
    03:06
  • HOMEWORK: Financial Statement Analysis
    10:11
  • Fundamentals of Python
    5 questions

  • Project Brief: Basketball Trends
    08:16
  • Preview03:31
  • Building Your First Matrix
    16:50
  • Dictionaries in Python
    14:20
  • Matrix Operations
    08:34
  • Your first visualization
    11:04
  • Expanded Visualization
    09:37
  • Creating Your First Function
    11:09
  • Advanced Function Design
    11:15
  • Preview11:17
  • Section Recap
    04:07
  • HOMEWORK: Basketball free throws
    08:43
  • Matrices
    5 questions

  • Preview08:25
  • Exploring your dataset
    10:51
  • Renaming Columns of a Dataframe
    02:56
  • Subsetting dataframes in Pandas
    16:31
  • Basic operations with a Data Frame
    09:49
  • Filtering a Data Frame
    18:52
  • Using .at() and .iat() (advanced tutorial)
    09:01
  • Introduction to Seaborn
    Preview10:47
  • Visualizing With Seaborn: Part 1
    10:05
  • Keyword Arguments in Python (advanced tutorial)
    10:42
  • Section Recap
    04:30
  • HOMEWORK: World Trends
    06:57
  • Data Frames
    5 questions

  • What is a Category data type?
    10:29
  • Working with JointPlots
    07:38
  • Histograms
    07:52
  • Stacked histograms in Python
    18:29
  • Creating a KDE Plot
    07:59
  • Working with Subplots()
    14:05
  • Violinplots vs Boxplots
    Preview08:55
  • Creating a Facet Grid
    12:28
  • Coordinates and Diagonals
    07:54
  • BONUS: Building Dashboards in Python
    16:31
  • Preview15:46
  • BONUS: Finishing Touches
    14:48
  • Section Recap
    05:37
  • HOMEWORK: Movie Domestic % Gross
    07:57
  • Advanced Visualization
    5 questions

  • Homework Solution Section 2: Law Of Large Numbers
    08:57
  • Homework Solution Section 3: Financial Statement Analysis (Part 1)
    10:30
  • Homework Solution Section 3: Financial Statement Analysis (Part 2)
    13:39
  • Homework Solution Section 4: Basketball Free Throws
    17:23
  • Homework Solution Section 5: World Trends (Part 1)
    15:45
  • Homework Solution Section 5: World Trends (Part 2)
    14:35
  • Homework Solution Section 6: Movie Domestic % Gross (Part 1)
    16:46
  • Homework Solution Section 6: Movie Domestic % Gross (Part 2)
    08:19
  • THANK YOU bonus video
    02:40

  • ***YOUR SPECIAL BONUS***
    01:55

Requirements

  • No prior knowledge or experience needed. Only a passion to be successful!

Description

Learn Python Programming by doing!

There are lots of Python courses and lectures out there. However, Python has a very steep learning curve and students often get overwhelmed. This course is different!

This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward.

After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples.

This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises.

In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course!

I can't wait to see you in class,

Sincerely,

Kirill Eremenko

Who this course is for:

  • This course if for you if you want to learn how to program in Python
  • This course is for you if you are tired of Python courses that are too complicated
  • This course is for you if you want to learn Python by doing
  • This course is for you if you like exciting challenges
  • You WILL have homework in this course so you have to be prepared to work on it

Featured review

HIMANSHU SHEKHAR
HIMANSHU SHEKHAR
4 courses
1 review
Rating: 5.0 out of 5a year ago
The instructor have a really good way to explain everything and if you want to learn from scratch, you can go ahead with this course. Update after 50%: Kirrill is knowledgeable instructor and knows ways to make stuff easy to understand.

Instructors

Kirill Eremenko
Data Scientist
Kirill Eremenko
  • 4.5 Instructor Rating
  • 460,926 Reviews
  • 1,703,210 Students
  • 44 Courses

My name is Kirill Eremenko and I am super-psyched that you are reading this!

Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes.

From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events.

To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you!

Ligency Team
Helping Data Scientists Succeed
Ligency Team
  • 4.5 Instructor Rating
  • 471,096 Reviews
  • 1,690,887 Students
  • 109 Courses

Hi there,

We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more!

We are here to help you stay on the cutting edge of Data Science and Technology.

See you in class,

Sincerely,

The Real People at Ligency

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