An Introduction to Machine Learning for Data Engineers

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THE REVIEWS ARE IN: Another fantastic course from a fantastic instructor. Very nicely stated, with just the proper amount of information. Mike’s explanations are straightforward and succinct, and he is well-versed in Google’s Cloud. Julie Johnson’s
Awesome! — Satendra
Excellent learning opportunity!! — Sri Lakshminarayana
Wonderful education… — Rajesh
Excellent – Dipthi
Straightforward and to the point. Fits a lot of information into brief, simple concepts/thoughts/scenarios. — Sam
The course was excellent. — Narsh
Excellent summary on machine learning. — Eli
Very useful for novices, with clear explanations of all concepts. Overall, an informative training session. Thank you very much! —Vikas
Excellent instruction. The concepts were clearly stated. — Jose
I enjoy how the course content has a real-world feel to it. This is really crucial. — Soham
I learned some new phrases and concepts about Machine Learning. Ideal for students who require a basic understanding of machine learning. – Akilan
This class is excellent for learning more about machine learning. – Neethu
As a newbie, I learned a lot about machine learning with data. Thank you, Mike. —Velumani
Very nicely described and helpful. — Vinoth
INTRODUCTION TO THE COURSE:
Thank you for visiting An Introduction to Machine Learning for Data Engineers. This course is part of my data engineering series. The course is required for my Tensorflow on the Google Cloud Platform for Data Engineers course.
This course will introduce you to the fundamentals of machine learning for data engineers. The course is designed to prepare students to take the Google Certified Data Engineering test.
This is NOT a broad course or a crash course on machine learning. This is a concentrated course for understanding the principles required to pass the Google Certified Data Engineering Exam.
At the moment, the only real-world credential for data and machine learning engineers is the Google Certified Data Engineer.
Machine learning is a sort of artificial intelligence (AI) that enables software programs to improve their accuracy in predicting events without being explicitly programmed. The crucial phrase there is “without being specifically designed.”
Supervised machine learning accounts for the great bulk of applied machine learning. The term used implies that you construct models in the real world. Supervised machine learning is a sort of machine learning in which models are built from existing data.
If you can obtain your data into a tabular format, such as that of an excel spreadsheet, most machine learning algorithms can model it.
We will study about the many sorts of algorithms utilized in the course. We will also go over machine learning-specific terminology. Every subject has its own jargon, and data science is no exception.
You’ll also discover why Python has emerged as the gold standard for developing real-world machine learning models.
We will also create a basic neural network and walk through the process and code step by step. Understanding the code will be less crucial than comprehending the significance and efficiency of a single artificial neuron.
*Five Reasons Why You Should Take This Course*
1) You Wish to Work as a Data Engineer
It is the most important job in the world. (Not simply in the computer world) Career advancement opportunities are unparalleled. You desire the freedom to go wherever you choose. You wish to be rewarded for your efforts. You want to be able to work from wherever. The list of advantages continues.
2) Certified Data Engineer by Google
Google is always one step ahead of the competition. If you look at a chronology of their achievements in the data domain, you could think they had a crystal ball. They were a decade ahead of everyone else. They are now the first and only cloud vendor to be certified in data engineering. I’ll go with Google based on their track record.
3) The rate of data growth is insane.
In the previous two years, 90% of the world’s data has been generated. Every day, businesses throughout the world do over 450 billion transactions. Every company collects around 2.5 Exabytes of data every day. Every month, that figure doubles.
4) Machine Learning Explained
Understanding the fundamentals of machine learning is necessary for a job as a data engineer, which is one of the hottest occupations on the globe. Google anticipates that data engineers will be able to create machine learning models. This course will cover all of the fundamentals of machine learning at a high level.
5) You want to be ahead of the competition.
The position of data engineer is relatively new. You are the first to be a part of this emerging industry as you study, build your abilities, and get certified. You are aware that being the first to get certified implies being the first to be employed and receiving the highest pay package.
Thank you for your interest in Machine Learning for Data Engineers: An Introduction.

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