Foundational Statistics for Data Science
Foundational Statistics for Data Science
“Data Scientist is a person who is better at statistics than any programmer and better at programming than any statistician.” - Josh Wills
Statistics for Data Science
In this course, we lay your foundation on Data Science. More often than not participants rush into learning data science without knowing what exactly they are getting into: this course will give you insights and clarity on what data science is all about.
Statistics, Math, Linear Algebra
If we talk in general about Data Science, then for a serious understanding and work we need a fundamental course in probability theory (and therefore, mathematical analysis as a necessary tool in probability theory), linear algebra and, of course, mathematical statistics. Fundamental mathematical knowledge is important in order to be able to analyze the results of applying data processing algorithms. There are examples of relatively strong engineers in machine learning without such a background, but this is rather the exception.
Data Mining and Data Visualization
Data Mining is an important analytic process designed to explore data. It is the process of analyzing hidden patterns of data according to different perspectives for categorization into useful information, which is collected and assembled in common areas, such as data warehouses, for efficient analysis, data mining algorithms, facilitating business decision making and other information requirements to ultimately cut costs and increase revenue.
Machine Learning
Machine learning allows you to train computers to act independently so that we do not have to write detailed instructions for performing certain tasks. For this reason, machine learning is of great value for almost any area, but first of all, of course, it will work well where there is Data Science.
Programming (Python & R)
We recommend all our students to learn both the programming languages and use them where appropriate since many Data Science teams today are bilingual, leveraging both R and Python in their work.
Through our Four-part series we will take you step by step, this is our first part which will lay your foundation. We will deal with the below sections in this Part 1:
Data Science Roles
Data Science Insights
Terminologies and Statistical Methods in Data Science
Discrete and Continuous random variables
Basics of descriptive statistics
Understanding Percentile
Lay the Foundation: Insights & Corporate Roles, Discrete & Continuous random variables, Descriptive Stats & Percentile!
Url: View Details
What you will learn
- You will gain a firm foothold of the fundamentals of Data Science. The course provides the entire toolbox you need to become a data scientist.
- You will understand the mathematics and statistics behind Machine Learning
- You will understanding the Octagonal Technical Facets of Data Science
Rating: 3.55
Level: Expert Level
Duration: 3 hours
Instructor: Sai Acuity Institute of Learning Pvt Ltd Enabling Learning Through Insight!
Courses By: 0-9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
About US
The display of third-party trademarks and trade names on this site does not necessarily indicate any affiliation or endorsement of hugecourses.com.
View Sitemap