Complete Python & Data Science Course for Absolute Beginners

The #1 course that is specifically tailored to beginners to build practical projects with Python and Data Science

4.35 (96 reviews)
Udemy
platform
English
language
Programming Languages
category
Mammoth Interactive
instructor
Complete Python & Data Science Course for Absolute Beginners
1,143
students
27 hours
content
Aug 2022
last update
$74.99
regular price

What you will learn

Learn Python from its very essential topics

Become an Absolute Python Professional

Develop your own Portfolio with the many python and python-related projects in the course

Learn concepts like Data Science and machine learning

Create Apps and Games with Python

Perform data mining

Build Dataframes using Apache Spark and Python with PySpark

Analyze data with Seaborn and Pandas

Why take this course?

Join our FREE masterclass ? Start your wonderful journey into coding and technology.

You might be wondering…

"Why should I learn programming?"

Programming is the #1 requested skill by employers with many jobs left unfilled yearly.

With our courses, anyone can learn to code.


Do you want to learn:

  • How to teach a self-driving car to navigate a highway?

  • How to detect objects, emotions and colors in videos?

  • How to restore images with code?

Build the next big machine learning app!

Learn how to:

  • build machine learning projects

  • add machine learning and data science to your resume

This bundle:

  • does not assume any level of experience

  • is perfect for beginners

THE COMPLETE SOURCE CODE WILL BE AVAILABLE.

No math or programming experience necessary.

  • Learn how to code in Python.

  • Build and run your first Python projects.

  • Think like a Python developer.

Learn how to use popular Python libraries:

  • NumPy - fundamental package for scientific computing in Python

  • Matplotlib's Pyplot - data visualization with plots, graphs and charts

  • Pandas - fast, powerful, flexible and easy to use data analysis and manipulation tool

Learn machine learning and artificial intelligence from scratch.

  • Learn how machine learning can solve problems in all disciplines.

  • Learn how to build a machine learning program.


Take your skills to the next level by building a huge range of models.

  • Build regression and classification models

  • Build artificial intelligence search algorithms

Build a full portfolio with practical machine learning projects.

  • Use Tensorflow 2.0 and Keras to build fun beginner projects.

  • Classify images, species of plants and more.


Dive into deep learning and master highly desirable skills.

  • Add projects to your resume in no time.

  • Learn a hireable skill and powerful technology

  • Help businesses find customer trends, leverage data to cut costs, and much more.

Requirements

  • No programming or machine learning experience needed - We'll teach you everything you need to know.

  • A Mac, PC or Linux computer.

We'll walk you through, step-by-step how to get all the software installed and set up

The only course you need to learn Machine Learning. With over 50,000 reviews, our courses are some of the HIGHEST RATED courses online!

This masterclass is without a doubt the most comprehensive course available anywhere online. Even if you have zero experience, this course will take you from beginner to professional.

Here's why:

  • This course is a taught by 3 instructors with decades of machine learning and programming experience.

  • We've taught over 1 million students how to code and many have gone on to become professional developers or start their own tech startup.

  • You'll save $72,000, the average cost of 6 coding bootcamps. You'll learn completely online at your own pace. You'll get lifetime access to content that never expires.

  • The course has been updated to be 2022 ready. You'll learn the latest tools and technologies used at large companies such as Google, Microsoft and Amazon.

We'll take you step-by-step through engaging video tutorials and teach you everything you need to know to succeed as a data analyst, machine learning specialist or similar.

The course includes 1080p HD video tutorials and builds your knowledge while making real-world projects.

Content

Python Language Fundamentals: Learn Python from scratch

Introduction
Intro To Python
Variables
Type Conversion Examples
Operators
Operators Examples
Collections
Lists
Multidimensional List Examples
Tuples Examples
Dictionaries Examples
Ranges Examples
Conditionals
If Statement Examples
If Statement Variants Examples
Loops
While Loops Examples
For Loops Examples
Functions
Functions Examples
Parameters And Return Values Examples
Classes and Objects
Classes Example
Objects Examples
Inheritance Examples
Static Members Example
Summary and Outro
Source Code

Graph data with python and Matplotlib

00. Course Intro
01. Intro To Pyplot
02. Installing Matplotlib
03. Basic Line Plot
04. Customizing Graphs
05. Plotting Multiple Datasets
06. Bar Chart
07. Pie Chart
08. Histogram
09. 3D Plotting
10. Course Outro
Source Code

Beginners data Analysis with Pandas

00. Panda Course Introduction
01. Intro To Pandas
02. Installing Pandas
03. Creating Pandas Series
04. Date Ranges
05. Getting Elements From Series
06. Getting Properties Of Series
07. Modifying Series
08. Operations On Series
09. Creating Pandas Dataframes
10. Getting Elements From Dataframes
11. Getting Properties From Dataframes
12. Dataframe Modification
13. Dataframe Operations
14 Dataframe Comparisons And Iteration
15. Reading CSVs
16.summary And Outro
Source Files

Data Mining with Python! Real-Life Data Science Exercises

Introduction to Data Mining
Project Files - Data Mining with Mammoth Interactive

2-1 Data Wrangling - A Complete Overview

Data Wrangling Demystified
Project Files - Data Wrangling with Mammoth Interactive

2-2 Data Mining Fundamentals

01. Cluster Analysis
02. Classification and Regression
03. Association and Correlation
04. Dimensionality Reduction
Project Files - Data Mining fundamentals with Mammoth Interactive

2-3 Frameworks Explained - Taming Big Data with Spark

01. Apache Spark - An Overview Of The Framework
02. Spark Key Functions
03. Spark Machine Learning
04. EXAMPLES - Using The Machine Learning Pipeline
Project Files - Frameworks with Mammoth Interactive

2-4 EXAMPLES - Mining and Storing Data

01. Text Mining
02. Network Mining
03. Matrix
04. SQL
Mining and Storing with Mammoth Interactive

2-5 NLP (Natural Language Processing)

01 NLP Data Cleaning
02. Count Vectorizer
03. NLP Example with Spam
04. Tweak Model with Spam Data
05. Pipeline with Spam Data
Project Files - NLP with Mammoth Interactive

2-6 Conclusion and Summary

06. Conclusion and Challenge
07 Conclusion Files - Mammoth Interactive

PySpark 1 - Build DataFrames with Python, Apache Spark and SQL

00 Project Preview
01 What Is Apache Spark
02 What Are Resilient Distributed Datasets
03A What Is A Dataframe
03B What You'll Need
Source Files

PySpark 2 - Build DataFrames from Spreadsheets

04 Start A Spark Session
05 Load Data As A CSV
06 Perform Basic Dataframe Operations
07 Format Dataframe Table
08 Perform Dataframe Math Operations
09 Perform Dataframe Queries
10 Build SQL Queries With Spark
Source Files

Python Data Analysis Bootcamp with Pandas and NLTK

00 Project Preview
01 Convert Csv File To A Python List
02 Tokenize Text Data
03 Find Most Popular Lemmatized Words
04 Build Dataframes Per Part Of Speech
05 Plot Word Frequency
Source Files

Exploratory Data Analysis Bootcamp with Python, Seaborn and Pandas

00 Project Preview
01 Load A Dataset
02 Analyze The Main Feature
03 Analyze Numerical Features
04 Analyze Categorical Features
Source Files

Visualize - Exploratory Data Analysis Bootcamp with Python, Seaborn and Pandas

01 Find Relationships Between Numerical Features
02 Find Relationships Between Categorical Features
03 Build Conditional Plots
Source Files

Overview - Introduction to Databases with Python SQL

00 Course Overview
01 What You'll Need
Source files

01 Introduction to data

01 Why You Must Know How To Work With Data
Source files

02 Entity Relationship Modeling (ERM)

01 How To Read An ER Model
Source files

03 Introduction to databases and relational databases

01 What Is A Database
02 What Is A Relational Database
Source files

04 How to build an organized database

01 How To Design Columns And Data Types
02 Use Normal Forms To Check Your Design
Source files

05 Build a SQLite database with Python

01 Build A SQLite Database With Python
02 Add An Entry To The Table With SQL
03 Add More Records To The Table
04 Build A Second Table For Cross-Referencing
05 Select Rows That Meet Conditions
Source files

Feature Analysis and Data Science with Stocks for Beginners

Course Overview
01 Load And Create Data
02 Perform Exploratory Data Analysis
03 Visualize Data With Different Plots
04 Analyze Features With More Plots
05 Build Plots With Seaborn
06 Build A Bokeh Plot
07 Build A 3D Scatter Plot
08 Rank Feature Importance
09 Compare Positive And Negative Returns
Source Files

The Definitive Python Time Series Analysis Masterclass

00 Project Preview
01 Load Crypto Prices Dataset
02 Visualize Bitcoin Price Trend
03 Predict Price With Facebook Prophet
04 Analyze Model Performance
05 Visualize Model Results
06 Predict Monthly Trend
07 Predict Weekly Trend
08 Compare Final Stock Price Of Different Strategies
Source Files

1). Stock Market Data Analysis and Visualization

00 Project Preview
01 Fetch Stock Data
02 Visualize Stock Data Features
03 Calculate Daily Return
04 Compare Returns Of Different Stocks
05 Compare Closing Prices
Source Files

2). Stock Market Data Analysis and Visualization

01 Visualize Standard Deviation And Expected Returns
02 Calculate Value At Risk
03 Monte Carlo Analysis To Estimate Risk
04 Visualize Price Distribution
Source Files

Scrape the Web - Python and Beautiful Soup Bootcamp

00 What Is Web Scraping
01 What You'll Need
Source Files
02 Build An HTML Webpage To Scrape
03 Select Data Structures From A Webpage
04 Extract URLs And Text
05 Work With Tags
06 Work With Attributes
07 Add Navigation To A String
08 Navigate HTML Contents
09 Find All Filter
Source Files

Build Interactive Python Dashboards with Plotly and Dash

01 Project Preview
02 What Is Plotly And Dash
03 What You'll Need
Source Files
01 Build A Dash App
02 Build A Graph In The Dash App
Source Files
01 Load Data From Vega Datasets
02 Build The Layout
03 Build A Chart With Altair
Source Files

Data Mining with Python and NumPy - Build a Video Recommender System

01 Project Preview
01 Build A Dataset
02 Compute Support And Confidence - If A Person Watches X, They Will Watch Y
03 Compute Support And Confidence For All Channels
04 Determine Which Videos Are Best To Recommend
Source Files

Reviews

Kambhampati
April 13, 2023
Because at the initial stage itself they were saying how to correct the errors with the help of google or stack overflow then what is the need of learning is it better to learn tricks
Charles
February 9, 2023
It's scary to think that by following these instructional videos I can be equipped with the skills to program Python.
Derek
February 1, 2023
very self explanatory as I am taking up a career in data science and i have to run programs in python.
Andre
January 18, 2023
So far so good. Although I have some fundamental knowledge of Python I did learn something new about Google Colab with this lecture.
Chuck
November 27, 2022
Good pace and I like the quizzes at the end of the sections. The projects really help develop an understanding of what you are working on without reading the descriptions of the reserved words.
veselin
November 20, 2022
Thank you for very interesting course. I think section of numpy should be added. Some sections should be updated. They are over four years old and use Python version 2. It will be nice to add reference with sort introduction of libraries used in the course.
David
October 25, 2022
This course does a great job of introducing Python and Data Science concepts; thus--giving enough understanding to propel one to learn more detailed theory to apply practical application toward Data Science application
Cheryl
August 6, 2022
Give real world and visual examples upfront at the very beginning. Examples of the code at work not just a named example in a bullet list. Say what is being typed: is it print left paren or print space left paren - this is probably only necessary for a one or two lessons
Stephanie
March 14, 2022
This course is described as being for "complete beginners". It is supposed to be designed for students who are completely new to Python and even programming in general. The instructor clearly has a great deal of knowledge in Python as well as other languages. Unfortunately, this seems to work against him in some cases, as he speeds through some topics that really need more discussion, almost seeming to forget that the student may not have ANY prior knowledge. For example, right from the start, I found myself wondering... - What is Google Colab? Never heard of it. Can you explain what it is and why you are choosing this environment? What other choices are there, or can I just use something like a general text editor? - How does Google Colab work? Can you describe the interface on at least a basic level? - Commenting? What does this do? I personally am familiar with commenting because I have been programming in HTML/CSS for years, but for those who are not, they just wasted a few seconds trying to figure out what you are doing and why. By the way, it looks like you are using a keyboard shortcut to comment quickly. Can you tell us what that shortcut is? - I got an error message when you didn't. Can you explain the anatomy of an error message so we know how to interpret it, especially when you have one appear on the screen. Since the content used to teach the fundamentals is being typed as part of the video (which is a good choice for a course like this), mistakes are going to happen, and that's a good thing because it illustrates what is going on, and a chance to re-emphasize why the code didn't work (whether intentional or not). However, please don't gloss over them, but rather explain why. We are typing with you and that first impression from an example that is actually incorrect needs to be addressed quickly. The instructor does give a lot of examples, but unfortunately they are not always consistent. Game references are good since we can likely relate to them, but pick an environment and stick with it so we can build on it. I realize licensing and copyright may present an issue to using a direct reference to something most of us know (Nintendo Mario games), but it would be easier to follow if the fundamentals of the game example were established early in the course and then consistently referenced from there on.

Coupons

DateDiscountStatus
6/23/202295% OFF
expired

Charts

Price

Complete Python & Data Science Course for Absolute Beginners - Price chart

Rating

Complete Python & Data Science Course for Absolute Beginners - Ratings chart

Enrollment distribution

Complete Python & Data Science Course for Absolute Beginners - Distribution chart

Related Topics

Python
Data Science
4500500
udemy ID
1/17/2022
course created date
2/3/2022
course indexed date
Bot
course submited by