In this one-week class, Coursera will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists.
This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods.
Course 4 of 5 in the Applied Data Science with Python Specialization.
Only minimal statistics background is expected, and the first course contains a refresh of these basic concepts. Learners with a formal training in Computer Science but without formal training in data science will still find the skills they acquire in these courses valuable in their studies and careers.
Institution: University of Michigan, via Coursera
In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them.
Learn scalable data management, evaluate big data technologies, and design effective visualizations.
Limited Time Special Pricing: 50% OFF Two months access.
Kickstart your Career in Data Science & ML. Master data science, learn Python & SQL, analyze & visualize data, build machine learning models.
This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library.
Master the basics of data analysis in Python. Expand your skillset by learning scientific computing with NumPy.
The price per month billed yearly.
You’ll learn different types of crowdfunding approaches, and receive detailed advice on what to do (and what not to do) when crowdfunding. You’ll also have the unique opportunity to go behind-the-scenes with key players in the field with exclusive interviews with the founder of Indiegogo and more.
This course is designed to give you a primer in the fundamentals of SQL and working with data so that you can begin analyzing it for data science purposes. You will begin to ask the right questions and come up with good answers to deliver valuable insights for your organization.