Machine Learning for Aspiring Data Scientists: Zero to Hero
What you'll learn
- Undertand the foundations of machine learning even if you're a total beginner
- Be able to pass the typical machine learning interviews for data science jobs
- Avoid rookie mistakes that waste companies' time and money
- Learn machine learning without spending time on mathematical proofs and outdated methods that don't come up in interviews or work.
- Build machine learning models with Python and Scikit-Learn
- Understand linear regression, neural networks, random forest, gradient boosting, support vector machines
Requirements
- No programming or advanced math experience required! You'll learn everything you need to know.
Description
This course will teach you the foundations of machine learning. The content was especially designed to help you pass machine learning interviews for data science jobs.
The course will help you:
Pass job interviews and technical quizzes
Avoid rookie mistakes that waste companies' time and money
Be prepared for real work.
Important stuff about this course:
You won't spend hours learning stuff that never comes up in a job interview.
Total beginners are welcome; coding experience or advanced math knowledge are not required.
It was designed by an industry expert who's been on the hiring side of the table and knows what companies are looking for.
This course will be of great help if you are:
A student who wants to prepare for work in data science after graduating.
An established professional or academic who wants to switch careers to data science.
A total beginner who wants to dabble in machine learning and data science for the first time.
How is this different from an academic course or a bootcamp?
In academic courses, your teacher spends hours speaking about calculus and linear algebra, but then none of that comes up in a job interview! That in-depth knowledge certainly has a place but is not what most companies are looking for.
In bootcamps you tend to learn how to use many tools but not how they work under the hood. This black-box knowledge is what companies want to avoid the most in applicants!
This course sits in between—you gain foundational knowledge and truly understand machine learning, without spending time on unimportant stuff.
Who this course is for:
- Aspiring data scientists who want to get their first job in the field.
- Software engineers who want to be involved in data science and machine learning.
- Researchers who want to make the move from academia to industry.
- Computer science graduates who want to dabble in data science.
Instructor
- 4.6 Instructor Rating
- 165 Reviews
- 6,815 Students
- 2 Courses
Emmanuel, PhD, is a computer scientist and AI expert. He runs his consulting business on data science and AI. He has worked with companies like Expedia, Vodafone, TUI fly, the French Space Agency and dozens of startups. He personally wrote some of Expedia’s AI-powered software to price hotel rooms, used by millions of travelers every day. During his past academic career he was one of the pioneers in using deep learning to automatically analyze the content of satellite images. He's passionate about teaching. In the past, he's given lectures on logic, theoretical computer science, machine learning, deep learning, and more.