Introduction to Data Science (IDS)

Introduction to Data Science

Dr. Daniel Gavrilovic

For more information about IDS, click on the IDS promotional video.

Course Syllabus PDF version attached below.

Course Description: Advances in technology have allowed us to collect massive amounts of data. A data scientist is a person who has the skills, knowledge and ability to extract actionable knowledge from the data, either for the good of society, advancement of science, profits in business, etc. This course will focus on practical applications of data analysis to give students concrete and applicable skills. It will engage in statistical inference using randomization and simulation techniques to enable students to learn about their world. Students will also be taught coding, using “R”, a programming language and RStudio, the interface.

Course Objectives: The main goal of IDS is to teach students to think critically about and with data. Upon completion of the course students will understand

How data are used by professionals to address real world problems
That data are used in all facets of modern life
How data support science to identify and tackle real-world problems in our communities
Analyze statistical graphics to identify patterns in data and to connect these patterns back to the real world
By treating photos, words, numbers, and sounds as data, we can gain insight into the real world

Student Expectations: Daily effort is considered a major part of your learning experience. Therefore, all assignments are to be completed and submitted on time. You are expected to learn, write, explain, and apply the concepts of this course. Analyze errors and ask for help when needed

COURSE OVERVIEW (subject to change)

Unit 1: Interpreting Categorical and Quantitative Data

Unit 2: Making Inferences and Justifying Conclusions

Unit 3: Conditional Probability and the Rules of Probability

Unit 4: Using Probability to Make Decisions

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