Statistics for Data Science
Statistics is used to process complex problems in the real world so that Data Scientists and Analysts can look for meaningful trends and changes in Data. In simple words, Statistics can be used to derive meaningful insights from data by performing mathematical computations on it.
Statistics for Data Science - Principles and Guidelines
This 1-day course provides you with essential principles and guidelines for leveraging statistical methods in the field of Data Science. Whether you're a beginner or an experienced practitioner, this course offers a comprehensive understanding of statistical concepts crucial for extracting valuable insights from diverse datasets. Participants will gain hands-on experience in applying statistical techniques to real-world scenarios, equipping them with the skills needed to make informed decisions and uncover hidden patterns within complex data sets. The course covers fundamental statistical principles, explores practical applications in data analysis, and provides guidance on interpreting statistical results accurately. By the end of the course, participants will have a solid foundation in statistical methods, enhancing their ability to contribute effectively to data-driven decision-making processes.
Value Proposition
Affordability
We aim to make data science training affordable to everyone.
Accreditation
Foundation class for MIRAR's Certified Associate in Data Science.
Practitioner's Focus
Training conducted with on-the-job perspective in mind.
Free Membership
Participants will be accepted as Associate Member.
This course will prepare you to:
Understanding
The objectives of a Statistics for Data Science Program.
Implementing
Statistical concepts and techniques in real-world data analysis and decision-making scenarios.
TBA