The Complete Python Course for Machine Learning Engineers
The Complete Python Course for Machine Learning Engineers, available at $59.99, has an average rating of 4.1, with 155 lectures, 10 quizzes, based on 516 reviews, and has 3019 subscribers.
You will learn about 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. This course is ideal for individuals who are If you want to become a machine learning engineer then this course is for you. or If you want to learn the basics of Python then this courses is for. or If you want something beyond the typical lecture style course then this course is for you. It is particularly useful for If you want to become a machine learning engineer then this course is for you. or If you want to learn the basics of Python then this courses is for. or If you want something beyond the typical lecture style course then this course is for you.
Enroll now: The Complete Python Course for Machine Learning Engineers
Summary
Title: The Complete Python Course for Machine Learning Engineers
Price: $59.99
Average Rating: 4.1
Number of Lectures: 155
Number of Quizzes: 10
Number of Published Lectures: 153
Number of Published Quizzes: 10
Number of Curriculum Items: 165
Number of Published Curriculum Objects: 163
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will 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.
Who Should Attend
- 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.
Target Audiences
- 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.
UPDATE: 8/26/2021 – I’ve added a second course.The second course included with this one is called The Fast Track Introduction to Python for Machine Learning Engineers.
I’ve added a second course to this one that will focus more on the machine learning aspect and less on core Python. There will be some overlap but that’s actually good news. The more you see something the easier it will be to remember.
I hope the two courses a compliment one another.
COURSE REVIEWS
This is the best hands-on online class I have ever taken. Very clear instructions. – Donato
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
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
This course does a good job in introducing machine learning in Python. – Vivek
Lesson are small, interactive, to the point and knowledge base. -Sanjay
Nice course on python programming & intro to libraries. – Sindhura
Yes. Accurate match for immediate requirements. Thank you! Looking forward to continuation courses.– Gregory
This course was very informative. Taught me about the open source models on which Machine Learning can be practiced. Kudos to the author. Great Job!!! – Mehar
Perfect explaining and perfect length, not too long explanations– Henrik
I loved the short format of the course. While that is a great thing there are some area which could have been a little longer. Overall, a very good course. – Raymond
Really well done !!!!! With this course the programming language itself can be learnt unrelated to any computational task.– Giovanni
The hands on examples made learning very easy. I learned a lot about Python and Machine Learning at the same time. I would totally recommend for beginners.– Lumi
Simple and easy to understand! – Pavan
Clear and easy to follow and understand the topic.– Dennis
COURSE OVERVIEW
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 worldthen 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 onlythe courses that are live. Here is a list of the courses that can be taken right now. Please take them in order. The knowledgebuilds from course to course.
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The Complete Python Course for Machine Learning Engineers (This one)
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Data Wrangling in Pandas for Machine Learning Engineers
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Data Visualization in Python for Machine Learning Engineers
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SciKit-Learn in Python for Machine Learning Engineers (NEW)
In this course we are going to learnPython 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 knowthe 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 cleansingis 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:
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Python basics from A-Z
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Lab integrated. Please don’t just watch. Learning is an interactive event. Go over every lab in detail.
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Real world Interviews Questions
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Data Wrangling overview. What is it? Pay attention to the basics, it’s what you’ll be doing most of your time.
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Build a basic model build in SciKit-Learn. We call these traditional models to distinguish them from deep learning models.
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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 standardfor 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 ahigh 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 Pythonyou’ll be completing labs that will build on what you’ve learned in the previous lesson so pleasedon’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!!
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: Is this Course for You?
Lecture 3: What is Python?
Lecture 4: Why Applied Machine Learning is Mostly Python
Lecture 5: Installing Python on Windows (Anaconda Distribution)
Lecture 6: Lab: Installing Python with Anaconda
Lecture 7: Lab: Connecting to Python
Lecture 8: Jupyter Notebook Anatomy – Menu Bar
Lecture 9: Jupyter Notebook Anatomy – Toolbar
Lecture 10: Lab: Code and Markup
Lecture 11: Summary
Lecture 12: Common Interview Questions – Section 1
Chapter 2: Variables and Operators
Lecture 1: The Comment in Python
Lecture 2: What's a Variable?
Lecture 3: Naming Variables
Lecture 4: Lab: Variables in Python
Lecture 5: The Assignment Operator
Lecture 6: Operators in Python
Lecture 7: Lab: Operators Notebook
Lecture 8: Data Types in Python
Lecture 9: String Formatting with the % Operator
Lecture 10: Type Casting in Python: Integers and Floating Points
Lecture 11: Type Casting in Python: Strings
Lecture 12: Lab: Casting Int and Float
Lecture 13: Summary
Lecture 14: Common Interview Questions – Section 2
Chapter 3: Advanced Data Types
Lecture 1: Lists
Lecture 2: Indexing Lists
Lecture 3: Modifying Items in Lists
Lecture 4: Slicing Lists
Lecture 5: Modifying Lists with Operators
Lecture 6: Removing an Item from a List
Lecture 7: Lab: Lists
Lecture 8: Tuples
Lecture 9: Dictionaries
Lecture 10: Accessing Dictionary Elements
Lecture 11: Using Functions to Access Elements
Lecture 12: Modifying Dictionaries
Lecture 13: Lab: Dictionaries
Lecture 14: Summary
Lecture 15: Common Interview Questions – Section 3
Chapter 4: Control Flow
Lecture 1: Conditional Statements
Lecture 2: Else/If Statement
Lecture 3: Lab: If Statement
Lecture 4: The For Loop
Lecture 5: Looping and the Dictionary
Lecture 6: Lab: Looping in Python
Lecture 7: While Loop
Lecture 8: The Break
Lecture 9: Continue Statement
Lecture 10: Lab: More Looping
Lecture 11: Summary
Lecture 12: Common Interview Questions – Section 4
Chapter 5: Functions and Modules
Lecture 1: What's a Function?
Lecture 2: User Defined Functions
Lecture 3: Lab: Working with Functions
Lecture 4: Variable Scope
Lecture 5: Default Parameter Values
Lecture 6: Variable Length Argument Lists
Lecture 7: Importing Modules
Lecture 8: Summary
Lecture 9: Common Interview Questions – Section 5
Chapter 6: Working with Files
Lecture 1: Download Simple Text File
Lecture 2: Open and Read Text Files
Lecture 3: Reading Text Files with a For Loop
Lecture 4: Using Buffer Size to Open and Read Text Files
Lecture 5: Lab: Working with Text Files
Lecture 6: Summary
Chapter 7: Basic Object Oriented Programming
Lecture 1: What is Object Oriented Programming?
Lecture 2: The Class
Lecture 3: Lab: Defining a Class in Python
Lecture 4: Classes, Objects and Instances
Lecture 5: Encapsulation
Lecture 6: Inheritance
Lecture 7: Summary
Lecture 8: Common Interview Questions – Section 7
Chapter 8: Pandas
Lecture 1: Data Wrangling Defined
Lecture 2: What is Pandas
Lecture 3: Loading our Dataset
Lecture 4: Data Types
Lecture 5: Columns, Rows and Cells
Lecture 6: Lab: Massaging Data in Pandas
Lecture 7: Summary
Lecture 8: Common Interview Questions – Section 8
Instructors
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Mike West
Creator of LogikBot
Rating Distribution
- 1 stars: 13 votes
- 2 stars: 24 votes
- 3 stars: 86 votes
- 4 stars: 212 votes
- 5 stars: 181 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?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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