Syllabus
Course Overview
Course Information
Lecture time: M/W 11:00 am - 12:20 pm in SST 220A, in-person lecture only.
Staff | Office Hours | |
Instructor: āYicong Huang Links to an external site. | Fri 4-5pm, ICS 458A | yicongh1 AT uci.edu |
Assistant: Shengquan Ni Links to an external site. | Tue 1-2pm, ICS 458A |
shengqun AT uci.edu |
Guest Lecturer: Chen Li | N/A |
chenli AT ics.uci.edu |
Lectures
Assignments
Assignment | Topic | Days | Due Date | Weight (of the entire course) |
1 | Tweet Analysis | 13 | Apr 14, 8 PM | 10% |
2 | Timeseries and Image Data Analysis | 13 | Apr 28, 8 PM (Task 3 due on May 5th, 8 PM) | 10% |
3 | Data Analysis with ML | 11 | May 19, 8PM | 10% |
Capstone Project
Days | Due Date | Weight (of the entire course) | |
Project Proposal | 5 | 05/23 | 5% |
Project Capstone Showcase | 17 | 06/05 | 35% |
Quizzes
We will not have midterms or finals. Instead, we will do in-class quizzes during lectures. We will announce quizzes ahead of time.
Date | Weight (of the entire course, the lowest one will be dropped) | |
1 | 04/15 | 10% |
2 | 05/01 | 10% |
3 | 05/15 | 10% |
4 | 06/03 | 10% |
Survey
You will participate in a survey evaluating the experience of using workflows for data science projects. The participation will account for 3% of your course grade, regardless of your feedback.
Texera Course Service
In this course, we will use Texera Links to an external site. system deeply to illustrate concepts, carry out assignments/projects, and facilitate communication.
Online Texera Service
Our team maintains a Texera live service at https://texera-ics80.ics.uci.edu. Please log in with your UCI email using the Google Login feature.
The service will be available to you every day 9 am - 9 pm. We will conduct maintenance outside this time. (Note: this means your execution may be force-killed after 9 pm.) You can check back this dashboard Links to an external site. for the latest status of the service.
Given that the Texera staff maintains this service and it is shared across the entire course, we urge you to handle it responsibly. Do not overwhelm it with large datasets or execute tasks that require a large amount of time (i.e. more than 1 hour). Your activities on the platform will be monitored. Activities including but not limited to crawling, cyber-attacking, and crypto-mining are strictly forbidden.
Texera Get Started Guide Links to an external site..
Account Activation Notice: After logging in with your UCI account, you might find that you are unable to access the dashboard. This is because your account requires manual activation by our team. Please allow for a delay of up to one day for this activation process to be completed.
Online Discussion Forum
Texera embeds a discussion forum, you can access it within Texera (backup independent link). This system is highly catered to getting you help fast and efficiently from classmates, the TA(s), and the instructor. Rather than emailing questions to any of us on the teaching staff, we'll ask you to post your questions on the Forum. Optionally, you can make a private post. Please ensure that the content you post is meaningful and adheres to ethical standards.
Grading Breakdown
Assignments: 30%
Quizzes: 30%
Capstone Project: 40%
Participation in Survey (Optional): extra 3%
Participation in EEE Class Evaluation (Optional): extra 1%
For all the graded projects and exams, if you disagree with the grading, you can discuss them with us within one week after they are returned. After that, all the grades will be finalized.
Prerequisites
This course is designed for individuals who may have little to no experience in coding, so there are no strict CS course prerequisites. The second half of the course will include an introduction to the programming language Python and its rich ecosystem for AI and ML. To better consume the course materials, we recommend you take ICS 31 and ICS 32 as they provide a basic introduction to programming.
Textbooks
Many online tutorials.
Working in Teams
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You will work individually on Assignments and Quizzes.
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You are expected to work in a team of 2 to collaborate on the Capstone Project. Work in groups will be graded on a per-group basis.
Policy on Academic Honesty
- All students will be expected to adhere to the UCI and ICS Academic Honesty policies (see https://conduct.uci.edu/students/academic-integrity/index.php for details). Any student found to be involved in cheating or aiding others in doing so will be academically prosecuted to the maximum extent possible: that means you will fail this course. Just say no to cheating!