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Data Foundations

Data is everywhere and is always being collected, which can be very intimidating.  This course helps you learn the basics of data so that you are able to remove any fear and replace it with knowledge on how to leverage data to make decisions and inform. Learn about all the places that data can be gathered, as well as how to manipulate, analyze and visualize it. No matter which industry or project you want to apply data analysis to, knowing the basics helps give you an advantage over the competition.

This course can be applied to the Data Analysis Certificate.

Instructor

Corey  Fritsch, MS

Corey Fritsch, MS

Corey Fritsch is an experienced data analyst with a passion for continued learning and research. Fritsch is currently pursuing his Doctor of Philosophy in Educational Statistics and Measurement at UW-Milwaukee, as well as graduate certificates in Applied Data Analysis and ... read more

Who Should Attend

Individuals who are pursuing the Data Analysis Certificate should take this course at the start of their program.  If you are currently working in a data-related field, you may take this course out-of-sequence based on consultation with the program manager. Contact information for the program manager can be found on this page.

Benefits and Learning Outcomes

  1. Obtain, manipulate and clean data
  2. Analyze and interpret data to create information and knowledge
  3. Visualize and communicate your data in a meaningful manner

Course Outline/Topics

 

Introduction to data analysis

  • What is data
  • Transition from data to information to knowledge
  • How data and statistics can be used to inform
  • How data is used in the world
  • Difference between data analysis, data analytics and data science
  • Where you can gather data from

Types of data

  • Quantitative vs qualitative
  • Subjective vs objective
  • Structured vs unstructured

Big Data

  • What defines Big Data
  • Who is using Big Data to drive decision making
  • How Big Data affects your life

Data cleanup and manipulation

  • What is messy data
  • What is missing data
  • Cleanup procedures

Data analysis

  • Descriptive analytics
  • Predictive analytics
  • Prescriptive analytics

Data visualization

  • Examples of data visualization
  • How it can be used to drive decision making
  • Charts
  • Infographics
  • Dashboards
  • Storytelling

Prerequisites

None

Notes

This is an online class with weekly recorded lectures, assignments and instructor feedback using online tools. Work any time of day as your schedule permits and submit assignments according to due dates. Weekly participation is required. An optional video call may be scheduled at a time mutually agreed upon by students and the instructor.

Testimonials

"I really enjoyed that the content changed based on what people already knew and wanted to learn more about. It was nice to not have a bunch of information that I already knew shown.

Corey was great at adjusting how he was talking, his examples and how detailed of a conversation there was about each topic."  —  Morgan Bauer, MilliporeSigma, Participant, February 2021

"Corey was very clear and organized in this class. He had energy to spare and was incredibly approachable. He made the class fun, but kept it productive."  —  Participant, February 2021

"This was the perfect intro course to data analytics."  —  Participant, February 2021

"Overall, I thought it was a great introductory course and taught very well by the instructor. I have a basic knowledge in all the topics that I expected."  —  Participant, February 2021

"Corey was definitely knowledgeable in the subject matter and kept everyone engaged. I would not hesitate to recommend him to others in the future."  —  Participant, February 2021

"This was my first virtual course and I actually think the format worked pretty well. I think having everyone use their cameras kept everyone engaged. Corey did a very nice job, especially for his first time teaching in this format."  —  Participant, September 2020

"I like how Corey was very thorough, open to going at the pace of the students, and always asking if we have questions. I like how he relates the content to his real-life experiences. I learned a lot of things from the course and it is a good refresher. The class allowed me to plan out what I need to gain in skills for data analysis."  —  Participant, January 2020

"I would have liked one more day (ish) to spend more time testing and applying knowledge. I enjoyed the quick quizzes. I appreciated that the other attendees were all at the same level. Corey did a great job getting us to engage – his personal insight tips and tricks were greatly appreciated and welcomed. Corey’s warm and fun style made the hours fly. It was really neat to see Christine and Becca standing by to help if needed. I didn’t expect that level of attention. Great course- well worth it! Thank you all!"  —  Cynthia McPhedran , MGIC, Participant, September 2020

"Loved this course it felt more like a refresher course of some of the foundational work. I understood this was meant to be the first course in the series so i took it out of order and now i can understand why as went over most of the topics in depth in the subsequent courses."  —  Daniel Silva, Participant, January 2020

"I liked working on the datasets we brought into the class. I enjoyed seeing Python and R and would welcome more of that. I know there are classes devoted to this."  —  Participant, January 2020

"Corey is an excellent instructor. He made it fun to learn"  —  Participant, January 2020

"What I liked most about the course was interaction with Corey. He laid the foundation of the course and then applied his knowledge and personality effectively. Nice and energetic person. Very well done, young man."  —  Participant, January 2020

"Instructor was very knowledgeable and provided many great resources for continued learning."  —  Participant, January 2020

"The instructor was well prepared, knowledgeable, and had great energy."  —  Participant, January 2020

"I really liked that all the concepts we learned can be applied right away in the workplace. The instructor did a good job of making sure he wasn’t going too quickly and emphasizing that it’s OK that we all are starting in a different place. Good high level overview, and I look forward to taking more in-depth classes."  —  Participant, September 2019

"The course content was well organized and the instructor is very experienced and professional. Also, the class setting in the fancy building in downtown and meeting other data people in different fields are also great additions that I enjoyed very much."  —  Suyu Lin, UWM, September 2019

"This class was very helpful and I will be able to take this information back to work with me."  —  Participant, September 2019

"I liked most that the instructor is actually working in the field and can bring a better perspective on the topic."  —  Participant, September 2019

"The class was great and I learned a lot. I liked the work portions on excel and gathering our own data."  —  Participant, September 2019

"I liked most the exposure to SQL, Python, and R. These are tools I have never used and can see how they can be very powerful as well as efficient. By using these tools, maybe more time can be spent on data analytics and data science."  —  Participant, September 2019

"Enjoyed the class. I was unsure of how “beginner” the class would be, and the instructor did a good job of adapting the material to the class. Some pieces I knew already but that was to be expected in a beginner course."  —  Participant, February 2019

"I really liked that I was able to talk to like-minded individuals about data and the various tools they use. It was also great to learn various tips and tricks!"  —  Participant, February 2019

"I really enjoyed the Data Foundations course. I thought it was well planned and easy to follow. I learned so much about data analytics and didn’t feel overloaded or rushed. The instructor (Corey Fritsch) was extremely down to earth and made timely adjustments to his curriculum based on the knowledge base of the students. Because of this, I’m confident I will be able to bring back what I learned and apply it to my daily work. Awesome class!"  —  Participant, February 2019

"I felt that this course was a good foundational basis/overview to the topic. Given people’s differing levels of familiarity/experience working with data this course could also act as a good foundation/level set of other courses (e.g. to some of the BA courses such as Using Data for Business Strategy and Decisions)."  —  Participant, February 2019

"The instructor was great. He has the right personality for this course, very lively, energetic, funny, and genuinely interested in the topics. The reasoning for the agree and not strongly agree on a couple organization questions, was due to this being the first class; however, he did a great job at reorganizing the class when he learned the type and skill levels of the students he was teaching. I will recommend this course and any other taught by Corey."  —  Participant, September 2018

"It was a very useful and entertaining overview. I’m looking forward to the rest of the courses in the certificate. I hope you continue to add more courses as technology and current use change."  —  Participant, September 2018

"I liked how it went from basic foundational information to the highly detailed examples. Showing how it all relates to work."  —  Participant, September 2018

"good intro class that covers basics of a lot of things about data"  —  Isabelle Kroes, Johnson Controls, September 2018

"The instructor was amazing and kept us engaged the entire class."  —  Participant, September 2018

Date: Sept 13-Oct 10

Delivery Method: Online

Platform: Canvas

Instructor: Corey Fritsch MS

Fee: $895

CEUs: 1.4

Enrollment Limit: 20

Program Number: 5020-13893

Note: This is an online class with weekly recorded lectures, assignments, and instructor feedback using online tools.  Work any time of day as your schedule permits and submit assignments according to due dates. Weekly participation is required. An optional video call may be scheduled at a time mutually agreed upon by students and the instructor.

Registration Deadline: Sept 13

Registration deadline has passed.
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