The Complete Python Course for Machine Learning Engineers
4.0 (450 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
2,791 students enrolled

The Complete Python Course for Machine Learning Engineers

The First Course in a Series for Mastering Python for Machine Learning Engineers
4.0 (450 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
2,791 students enrolled
Created by Mike West
Last updated 1/2020
English
English [Auto]
Current price: $13.99 Original price: $19.99 Discount: 30% off
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30-Day Money-Back Guarantee
This course includes
  • 1.5 hours on-demand video
  • 43 articles
  • 5 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • You'll learn everything you need to know about Python for authoring basic machine learning models.
  • You'll work through hands on labs that will test the skills you learned in the lessons.
  • You'll learn all the Python vernacular you need to take you skills to the next level.
  • You'll build a basic Deep Neural Network in Python line by line.
  • You'll use Scikit-Learn to Build a Traditional Machine Learning Model
  • You'll understand why Python has become the Gold Standard in the Machine Learning Space.
Course content
Expand all 108 lectures 02:14:56
+ Introduction
12 lectures 18:36

This is the course into. 

What's the course about? 

Preview 01:32

Do you need to learn Python? 

If you want to be a machine learning engineer, data scientist or data engineer then this course is for you. 

Preview 01:06

Why learn Python? 


Preview 01:33

In this lesson let's learn why most applied machine learning is Python. 

Preview 01:49
Python Skills Evaluation
25 questions

In this lecture let's install Python on our Windows computer. 

Installing Python on Windows (Anaconda Distribution)
02:28

Let's install Python on a Windows laptop the easy way. 

Lab: Installing Python with Anaconda
01:06

Let's connect to our web IDE. 

Lab: Connecting to Python
00:35

Let's learn how to navigate the menu bar on our Jupyter notebooks. 

Jupyter Notebook Anatomy - Menu Bar
02:58

Let's learn the most frequently used icon... called our toolbar. 

Jupyter Notebook Anatomy - Toolbar
02:40

Markup is text like HTML. 

Let's learn how to use it in our Notebooks. 

Lab: Code and Markup
01:05
Summary
00:46
Quiz
10 questions
Common Interview Questions - Section 1
00:55
+ Variables and Operators
14 lectures 21:20

Let's learn how to document our code with a simple comment. 

Preview 00:55

We use variable all the time. 

What are they? 

What's a Variable?
01:09

Let's learn a commonly used naming convention for your variables. 

Preview 01:46

Let's complete our lab on variables. 

Lab: Variables in Python
01:09

It looks like an equals sign but not in Python. 

Let's learn what it is in this lesson. 

The Assignment Operator
01:24

What is an operator and how do we use them? 

Operators in Python
01:22

Let's learn about operators in this short lesson. 

Lab: Operators Notebook
00:57

What's a data type and how many core data types exist in Python? 

Data Types in Python
01:50

Let's format some data in this lesson. 

String Formatting with the % Operator
01:31

Sometimes we need int and sometimes we need strings and sometimes we need to go between the two of them. 

Let's learn how in this lesson. 

Preview 02:06

How to we change int to strings in Python? 

Type Casting in Python: Strings
03:52

Let's get some hands on with casting data types. 

Lab: Casting Int and Float
01:21
Summary
00:56
Quiz
10 questions
Common Interview Questions - Section 2
00:59
+ Advanced Data Types
15 lectures 18:50

What's a list and why is it so common? Let's find out. 

Lists
01:36

How do we speed up the retrieval of our Lists? 

How do we access our lists? 

Indexing Lists
01:42

Let's manipulate some items in our lists. 

Modifying Items in Lists
00:51

What does slicing mean and why is it so useful? 

Slicing Lists
02:17

Lit's modify some lists. 

Modifying Lists with Operators
02:19

How do we remove items from out lists? Let's learn how in this short lesson. 

Removing an Item from a List
01:08

Let's get our hands dirty with lists. 

Lab: Lists
01:11

What's the difference between Tulpes and lists? It's important so let's find out. 

Tuples
01:03

What's a dictionary in Python? 

Dictionaries
01:11

How do we access items in our dictionaries? Let's find out in this lesson. 

Accessing Dictionary Elements
01:05

Let's learn about some great functions for our dictionaries. 

Using Functions to Access Elements
01:23

We need to modify dictionaries just like we need to modify lists. 

Let's learn how in this lesson. 

Modifying Dictionaries
00:42

Hands on with Dictionaries. Don't skip these labs. 

Lab: Dictionaries
00:57
Summary
00:52
Quiz
10 questions
Common Interview Questions - Section 3
00:32
+ Control Flow
12 lectures 13:30

Let's learn what conditional statement are. 

Conditional Statements
01:53

The most famous of all control statements. 

Let's learn about them in this brief lesson. 

Else/If Statement
01:34

In this short lab let's get our hands dirty with the If statement. 

Lab: If Statement
00:42

Another famous conditional statement is the for loop. 

Let's learn about it in this lesson. 

The For Loop
00:52

Let's loop over a dictionary. 

Looping and the Dictionary
01:03

Time to get our hands dirty with the loop. 

Lab: Looping in Python
01:54

The while loop is used often but has a small caveat. 

Let's find out what that is. 

While Loop
01:21

Let's stop a for loop in it's track. 

The Break
00:22

Let's move on after a break in our conditional statement. 

Continue Statement
01:22

Can't get enough of those loops in this course. 

Lab: More Looping
01:20
Summary
00:44
Quiz
10 questions
Common Interview Questions - Section 4
00:22
+ Functions and Modules
9 lectures 11:24

Functions are a major part of Python. 

Let's define them in this lesson. 

What's a Function?
01:07

In Python we can create our own functions. 

Let's learn how in this lesson. 

User Defined Functions
01:28

Let's do a lab on functions. 

Lab: Working with Functions
01:28

Variables have different scope inside function. 

Let's learn about local and global scope in this lesson. 

Variable Scope
01:24

We can have default parameters in functions. 

Let's learn how to use them. 

Default Parameter Values
00:57

Long name but easy to understand. 

Let's learn about variable length argument lists. 

Variable Length Argument Lists
01:33

Core to understand and working with Python. 

It's very simple so let's understand what they do. 

Importing Modules
01:41
Summary
00:43
Quiz
9 questions
Common Interview Questions - Section 5
01:02
+ Working with Files
6 lectures 05:42
Download Simple Text File
00:07

Let's open and read an existing text file in this lesson. 

Open and Read Text Files
01:27

Let's read through our text file using a for loop. 

Reading Text Files with a For Loop
01:11

Let's specify the size of memory we want our code to use. 

Using Buffer Size to Open and Read Text Files
01:23

Let's walk through a quick lab on working with text files. 

Lab: Working with Text Files
01:07
Summary
00:27
+ Basic Object Oriented Programming
8 lectures 09:48

Let's define what OOP is pictorially. 

What is Object Oriented Programming?
01:28

We need to understand the class in OOP. 

The Class
01:14

Let's create our own class in Python. 

Lab: Defining a Class in Python
01:08

Let's talk about the fundamentals of OOP. 

Classes, Objects and Instances
02:15

What is encapsulation? 

Encapsulation
01:14

Let's define inheritance. 

Inheritance
01:04
Summary
00:54
Quiz
10 questions
Common Interview Questions - Section 7
00:30
+ Pandas
8 lectures 09:37

Data wrangling is what machine learning engineers spend most of their time doing. 

Let's define what that is. 

Data Wrangling Defined
00:33

Let's define pandas in the lecture. 

What is Pandas
01:06

Let's load out data set in Pandas. 

Loading our Dataset
02:01

What data types are there in pandas? 

Let's find out. 

Data Types
01:20

Let's massage our tabular data set. 

Columns, Rows and Cells
01:31

Let's work through our lab in Pandas. 

Lab: Massaging Data in Pandas
01:37
Summary
00:50
Quiz
10 questions
Common Interview Questions - Section 8
00:37
+ SciKit-Learn
11 lectures 11:42
Download Raw Titanic Data Set
00:07

Let's define this set of libraries. 

What is Sci-kit Learn?
01:26

Let's explore our data set via Pandas. 

Data Exploration in Pandas
02:19

Let's alter or wrangle our data in Pandas. 

Data Wrangling in Pandas
01:00

Let's learn about the X and Y axes. 

The X and y Axis
00:43

Let's split our data set up into different sections. 

Train, Test and Split
01:27

Classifiers are our models in Sci-Kit Learn. 

Let's learn about them in this lesson. 

Importing our Classifier
01:02

Let's fit and predict our model. 

Fit and Predict
01:12

Let's work through our lab. 

Lab: SciKit-Learn
01:40
Summary
00:14
Quiz
5 questions
Common Interview Questions - Section 9
00:31
+ Keras
13 lectures 14:23
Installing Keras (Anaconda Distribution for Windows)
02:50
Download Cleansed BikeBuyer Data Set
00:07

Keras is used for building deep learning models. 

Lets define it in this lesson. 

What is Keras?
00:49

Let's import our dataset. 

Import, Create and Load
01:25

Let's wrangle or massage our data. 

Data Wrangling
01:02

Let's define our target variable. 

Defining the Target Variable and Training Data
01:32

Let's define our Keras model. 

Model Definition
01:18

Let's compile and fit our model. 

Model Compilation
00:43

Let's build our lab. 

Lab: Keras
02:46
Summary
00:22
Quiz
10 questions
Common Interview Questions - Section 10
00:43
Congratulations and Thank You
00:25
Bonus Lecture: Data Wrangling in Pandas
00:19
Requirements
  • A basic understanding of programming
  • Desire to learn Python
Description

Reviews 

"I took a few of your courses and you are an amazing teacher. Your courses have brought me up to speed on how to create databases and how to interact and handle Data Engineers and Data Scientists. I will be forever grateful."  -Tony

"By taking this course my perception has changed and now data science for me is more about data wrangling. Thank you, Mike:)"  -Archit

"This is the best hands-on online class I have ever taken. Very clear instructions." - Donato

I have now finished the first one, The complete python course and I have found it extremely structured and clear. I really thank you for your efforts in making these videos. I will now move on to Pandas. I am also looking out for jobs in order to start my career in this exciting field. - Gurukiran A

"I am really thankful to the instructor for creating such a nice and interactive course, thanks again." - Arun

Welcome to The Complete Course for Machine Learning Engineers.

This series of courses is the only real world path to attaining a job as a machine learning engineer.  Machine learning engineers don't build models every day.  

If you want to work in the real world then focus on learning Python. That's what this course is... Python!!!

This is the first course in a series of courses designed to prepare you for a real-world career as a machine learning engineer. 

I'll keep this updated and list only the courses that are live.  Here is a list of the courses that can be taken right now.  Please take them in order.  The knowledge builds from course to course. 

  • The Complete Python Course for Machine Learning Engineers (This one) 

  • Data Wrangling in Pandas for Machine Learning Engineers

  • Data Visualization in Python for Machine Learning Engineers

  • SciKit-Learn in Python for Machine Learning Engineers (NEW)

In this course we are going to learn Python using a lab integrated approach. Programming is something you have to do in order to master it. You can't read about Python and expect to learn it. 

If you take this course from start to finish you'll know the core foundations of Python, you'll understand the very basics of data cleansing and lastly you'll build a traditional machine learning model and a deep learning model. 

While the course is centered on learning the basics of Python you'll get to see how data cleansing is applied to a data set and how a traditional machine learning model and a deep learning model are built. 

This course is an applied course on machine learning. Here' are a few items you'll learn: 

  • Python basics from A-Z

  • Lab integrated. Please don't just watch. Learning is an interactive event.  Go over every lab in detail. 

  • Real world Interviews Questions

  • Data Wrangling overview. What is it? Pay attention to the basics, it's what you'll be doing most of your time. 

  • Build a basic model build in SciKit-Learn. We call these traditional models to distinguish them from deep learning models. 

  • Build a basic Keras model. Keras is becoming the go to Python library for building deep learning models. 

If you're new to programming or machine learning you might ask, why would I want to learn Python? Python has become the gold standard for building machine learning models in the applied space. The term "applied" simply means the real world. 

Machine learning is a type of artificial intelligence (AI) that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. The key part of that definition is “without being explicitly programmed.”

If you're interested in working as a machine learning engineer, data engineer or data scientist then you'll have to know Python. The good news is that Python is a high level language. That means it was designed with ease of learning in mind. It's very user friendly and has a lot of applications outside of the ones we are interested in. 

In The Complete Course for Machine Learning Engineers we are going to start with the basics. You'll learn how to install Python all the way through building a simple deep learning model using the skills you've learned. 

As you learn Python you'll be completing labs that will build on what you've learned in the previous lesson so please don't skip any. 

                                                               *Five Reasons to take this Course.*

1) You Want to be a Machine Learning Engineer

It's one of the most sought after careers in the world. The growth potential career wise is second to none. You want the freedom to move anywhere you'd like. You want to be compensated for your efforts. You want to be able to work remotely. The list of benefits goes on. Without a solid understanding of Python you'll have a hard time of securing a position as a machine learning engineer. 

2) The Google Certified Data Engineer 

Google is always ahead of the game. If you were to look back at a timeline of their accomplishments in the data space you might believe they have a crystal ball. They've been a decade ahead of everyone.  Now, they are the first and the only cloud vendor to have a data engineering certification. With their track record I'll go with Google.  You can't become a data engineer without learning Python. 

3) The Growth of Data is Insane 

Ninety percent of all the world's data has been created in the last two years. Business around the world generate approximately 450 billion transactions a day. The amount of data collected by all organizations is approximately 2.5 exabytes a day. That number doubles every month.  Almost all real world machine learning is supervised. That means you point your machine learning models at clean tabular data. Python has libraries that are specific to data cleansing. 

4) Machine Learning in Plain English

Machine learning is one of the hottest careers on the planet and understanding the basics is required to attaining a job as a data engineer.  Google expects data engineers and their machine learning engineers to be able to build machine learning models. In this course, you'll learn enough Python to be able to build a deep learning model. 

5) You want to be ahead of the Curve 

The data engineer and machine learning engineer roles are fairly new.  While you’re learning, building your skills and becoming certified you are also the first to be part of this burgeoning field.  You know that the first to be certified means the first to be hired and first to receive the top compensation package. 

Thanks for interest in The Complete Python Course for Machine Learning Engineers 

See you in the course!!


Who this course is for:
  • If you want to become a machine learning engineer then this course is for you.
  • If you want to learn the basics of Python then this courses is for.
  • If you want something beyond the typical lecture style course then this course is for you.