Getting Started
Track your degree and line up your desired courses for the next few semesters
I built this doc to better visualize and understand the dependencies and trade offs while selecting courses for the upcoming semester.
To get started, first mark off any courses that you’ve already completed:
Mark off completed courses
Courses that are required are shaded differently than electives.
Category
Mark Completed
Course
Name
Required
Data Science Core
3
SIADS 501
Being a Data Scientist
SIADS 503
Data Science Ethics
SIADS 601
Qualitative Inquiry
Analytic Technique
13
SIADS 502
Math Methods for Data Science
SIADS 532
Data Mining I
SIADS 542
Supervised Learning
SIADS 543
Unsupervised Learning
SIADS 602
Math Methods II
SIADS 630
Causal Inference
SIADS 631
Experiment Design and Analysis
SIADS 632
Data Mining II
SIADS 642
Deep Learning
SIADS 643
Machine Learning Pipelines
SIADS 644
Reinforcement Learning Algorithms
SIADS 652
Network Analysis
SIADS 655
Natural Language Processing
Computational Methods
5
SIADS 505
Data Manipulation
SIADS 511
SQL & Databases
SIADS 515
Big Data: Efficient Data Processing
SIADS 516
Big Data: Scalable Data Processing
SIADS 611
Database Architectures & Technologies
Communication
5
SIADS 521
Visual Exploration of Data
SIADS 522
Information Visualization I
SIADS 523
Communicating Data Science Results
SIADS 524
Presenting Uncertainty
SIADS 622
Information Visualization II
Data Science Application
5
SIADS 680
Learning Analytics
SIADS 682
Social Media Analytics
SIADS 685
Search and Recommender Systems
SIADS 687
Sports Analytics
SIADS 688
Data Science for Social Good
Milestone and Capstone
5
SIADS 591
Project I: synthesis of computational techniques to collect and process big data
SIADS 592
Project II: synthesis of analytics and machine learning techniques to analyze data and present results
SIADS 694
Project II: synthesis of analytics and machine learning techniques to analyze data and present results
SIADS 695
Project II: synthesis of analytics and machine learning techniques to analyze data and present results
SIADS 697
Project III: capstone that applies end-to-end data science techniques to real world scenarios
And then you can proceed to to select courses for the upcoming semester(s). Or you can view your towards completing the Michigan Masters of Applied Data Science degree.
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