Jason Ernst
Department of Computer Science
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5.0
Overall Rating
Based on 1 User
Easiness 5.0 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 3.0 / 5 How clear the class is, 1 being extremely unclear and 5 being very clear.
Workload 5.0 / 5 How much workload the class is, 1 being extremely heavy and 5 being extremely light.
Helpfulness 5.0 / 5 How helpful the class is, 1 being not helpful at all and 5 being extremely helpful.

TOP TAGS

  • Uses Slides
  • Engaging Lectures
  • Participation Matters
GRADE DISTRIBUTIONS
100.0%
83.3%
66.7%
50.0%
33.3%
16.7%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

ENROLLMENT DISTRIBUTIONS
Clear marks

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Reviews (1)

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Quarter: Winter 2022
Grade: NR
COVID-19 This review was submitted during the COVID-19 pandemic. Your experience may vary.
March 24, 2022

There were two professors that taught this class (Bogdan Pasaniuc and Jason Ernst), switching off every week to cover topics that they are experts in. The content is interesting and more importantly, it exposes you to relevant papers in Bioinformatics that may not be in the same line of research you are conducting (if you are in CompBio research). The 7 homeworks were graded based on participation and were fairly simple and short, released on Tuesday and due on Thursday (of the same week). There was also a final project, for which they provided many sample projects as well as allowing you to make a novel project off of your research. There was one mini presentation on your chosen project in week 7 (5 minutes) and the final project presentation was in week 10 (10 minutes). There were no exams and overall was an interesting and low workload course. (The professors are also super nice and are willing to answer any questions you have)

Grading:
Participation: 20%
Homework: 30%
Final Project: 50%

Course content:
Week 1: Overview / Final Project
Week 2: Clustering / Classification
Week 3: Ancestry Inference
Week 4: HMMs
Week 5: Disease Mapping
Week 6: Regulatory Sequence Modeling
Week 7: Initial project presentations
Week 8: Genetic Risk Prediction
Week 9: Graphical Models
Week 10: Final Project Presentations

Helpful?

0 0 Please log in to provide feedback.
COVID-19 This review was submitted during the COVID-19 pandemic. Your experience may vary.
Quarter: Winter 2022
Grade: NR
March 24, 2022

There were two professors that taught this class (Bogdan Pasaniuc and Jason Ernst), switching off every week to cover topics that they are experts in. The content is interesting and more importantly, it exposes you to relevant papers in Bioinformatics that may not be in the same line of research you are conducting (if you are in CompBio research). The 7 homeworks were graded based on participation and were fairly simple and short, released on Tuesday and due on Thursday (of the same week). There was also a final project, for which they provided many sample projects as well as allowing you to make a novel project off of your research. There was one mini presentation on your chosen project in week 7 (5 minutes) and the final project presentation was in week 10 (10 minutes). There were no exams and overall was an interesting and low workload course. (The professors are also super nice and are willing to answer any questions you have)

Grading:
Participation: 20%
Homework: 30%
Final Project: 50%

Course content:
Week 1: Overview / Final Project
Week 2: Clustering / Classification
Week 3: Ancestry Inference
Week 4: HMMs
Week 5: Disease Mapping
Week 6: Regulatory Sequence Modeling
Week 7: Initial project presentations
Week 8: Genetic Risk Prediction
Week 9: Graphical Models
Week 10: Final Project Presentations

Helpful?

0 0 Please log in to provide feedback.
1 of 1
5.0
Overall Rating
Based on 1 User
Easiness 5.0 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 3.0 / 5 How clear the class is, 1 being extremely unclear and 5 being very clear.
Workload 5.0 / 5 How much workload the class is, 1 being extremely heavy and 5 being extremely light.
Helpfulness 5.0 / 5 How helpful the class is, 1 being not helpful at all and 5 being extremely helpful.

TOP TAGS

  • Uses Slides
    (1)
  • Engaging Lectures
    (1)
  • Participation Matters
    (1)
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