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The Complete Python Course for Machine Learning Engineers

The First Course in a Series for Mastering Python for Machine Learning Engineers
Instructor:
Mike West
2,285 students enrolled
English [Auto-generated]
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.

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

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!!

Introduction

1
Introduction

This is the course into. 

What's the course about? 

2
Is this Course for You?

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. 

3
What is Python?

Why learn Python? 


4
Why Applied Machine Learning is Mostly Python

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

5
Python Skills Evaluation
6
Installing Python on Windows (Anaconda Distribution)

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

7
Lab: Installing Python with Anaconda

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

8
Lab: Connecting to Python

Let's connect to our web IDE. 

9
Jupyter Notebook Anatomy - Menu Bar

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

10
Jupyter Notebook Anatomy - Toolbar

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

11
Lab: Code and Markup

Markup is text like HTML. 

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

12
Summary
13
Quiz
14
Common Interview Questions - Section 1

Variables and Operators

1
The Comment in Python

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

2
What's a Variable?

We use variable all the time. 

What are they? 

3
Naming Variables

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

4
Lab: Variables in Python

Let's complete our lab on variables. 

5
The Assignment Operator

It looks like an equals sign but not in Python. 

Let's learn what it is in this lesson. 

6
Operators in Python

What is an operator and how do we use them? 

7
Lab: Operators Notebook

Let's learn about operators in this short lesson. 

8
Data Types in Python

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

9
String Formatting with the % Operator

Let's format some data in this lesson. 

10
Type Casting in Python: Integers and Floating Points

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. 

11
Type Casting in Python: Strings

How to we change int to strings in Python? 

12
Lab: Casting Int and Float

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

13
Summary
14
Quiz
15
Common Interview Questions - Section 2

Advanced Data Types

1
Lists

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

2
Indexing Lists

How do we speed up the retrieval of our Lists? 

How do we access our lists? 

3
Modifying Items in Lists

Let's manipulate some items in our lists. 

4
Slicing Lists

What does slicing mean and why is it so useful? 

5
Modifying Lists with Operators

Lit's modify some lists. 

6
Removing an Item from a List

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

7
Lab: Lists

Let's get our hands dirty with lists. 

8
Tuples

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

9
Dictionaries

What's a dictionary in Python? 

10
Accessing Dictionary Elements

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

11
Using Functions to Access Elements

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

12
Modifying Dictionaries

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

Let's learn how in this lesson. 

13
Lab: Dictionaries

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

14
Summary
15
Quiz
16
Common Interview Questions - Section 3

Control Flow

1
Conditional Statements

Let's learn what conditional statement are. 

2
Else/If Statement

The most famous of all control statements. 

Let's learn about them in this brief lesson. 

3
Lab: If Statement

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

4
The For Loop

Another famous conditional statement is the for loop. 

Let's learn about it in this lesson. 

5
Looping and the Dictionary

Let's loop over a dictionary. 

6
Lab: Looping in Python

Time to get our hands dirty with the loop. 

7
While Loop

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

Let's find out what that is. 

8
The Break

Let's stop a for loop in it's track. 

9
Continue Statement

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

10
Lab: More Looping

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

11
Summary
12
Quiz
13
Common Interview Questions - Section 4

Functions and Modules

1
What's a Function?

Functions are a major part of Python. 

Let's define them in this lesson. 

2
User Defined Functions

In Python we can create our own functions. 

Let's learn how in this lesson. 

3
Lab: Working with Functions

Let's do a lab on functions. 

4
Variable Scope

Variables have different scope inside function. 

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

5
Default Parameter Values

We can have default parameters in functions. 

Let's learn how to use them. 

6
Variable Length Argument Lists

Long name but easy to understand. 

Let's learn about variable length argument lists. 

7
Importing Modules

Core to understand and working with Python. 

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

8
Summary
9
Quiz
10
Common Interview Questions - Section 5

Working with Files

1
Download Simple Text File
2
Open and Read Text Files

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

3
Reading Text Files with a For Loop

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

4
Using Buffer Size to Open and Read Text Files

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

5
Lab: Working with Text Files

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

6
Summary

Basic Object Oriented Programming

1
What is Object Oriented Programming?

Let's define what OOP is pictorially. 

2
The Class

We need to understand the class in OOP. 

3
Lab: Defining a Class in Python

Let's create our own class in Python. 

4
Classes, Objects and Instances

Let's talk about the fundamentals of OOP. 

5
Encapsulation

What is encapsulation? 

6
Inheritance

Let's define inheritance. 

7
Summary
8
Quiz
9
Common Interview Questions - Section 7

Pandas

1
Data Wrangling Defined

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

Let's define what that is. 

2
What is Pandas

Let's define pandas in the lecture. 

3
Loading our Dataset

Let's load out data set in Pandas. 

4
Data Types

What data types are there in pandas? 

Let's find out. 

5
Columns, Rows and Cells

Let's massage our tabular data set. 

6
Lab: Massaging Data in Pandas

Let's work through our lab in Pandas. 

7
Summary
8
Quiz
9
Common Interview Questions - Section 8
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