Exploring Digital Information Technologies for Non-Engineers
Spring 2025
Course Description
This course will give students from outside of Engineering an under-the-hood view of 12 important technologies that will impact their daily lives in the next decade.
- WiFi and Cellular networks
- Internet
- File Systems
- Search Engines
- Recommendation Engines
- Social Networks
- Machine Learning
- Authentication and Security
- Computer Vision and Image Processing
- Speech Recognition and Natural Language Processing
- Self-driving Cars
- Augmented and Virtual Reality
For each technology, students will
1. understand the core technical challenges in realizing the technology
2. gain intuition on how the challenges are being solved
3. appreciate how such technologies translate to business and revenue, and
4. identify implications in areas such as privacy, fairness, policy, ethics, and other paradigm shifts.
Technical subjects to be considered include basics of sensing, computing, communication, and control, the four pillars of technology. To help students better relate to the topics discussed in the course, each technology will highlighted one or more well-established companies using/promoting the technology (e.g., Comcast, ATT, Microsoft, Google, Amazon, Meta, Verisign, ADT, Apple, OpenAI, Tesla, etc.).
Logistics
Lectures
Mondays & Wednesdays, 11:00pm - 11:50am at 3081 Electrical & Computer Eng Bldg (ECEB)
Labs
Fridays, 10:00am - 11:50am or 12:00pm - 1:50pm at 1009 Mechanical Engineering Laboratory (MEL)
We will use Wolfram Mathematica in the labs. This software is available on the computers in the MEL 1009 computer lab. You can access it using your netID and password.
You can also download and install Wolfram Mathematica on your computers from here (using your netID and password).
Labs will be submitted and graded using Canvas. Details about the submission process will be provided during the first lab.
Communication
We will use Canvas for all communications in this course. We will post important announcements, links to interesting resources, discussion threads (responses to which will count as class participation), class participation and homework assignments and also respond to student questions on Canvas.
We will also respond to student emails.
Office Hours
Instructor: Abrita Chakravarty
Mondays & Wednesdays, 11:50am - 12:30pm or by appointment at 1060 Electrical & Computer Eng Bldg
TA: Sattwik Basu
Tuesdays, 4:00pm - 5:00pm at 4034 Electrical & Computer Eng Bldg
Calendar
Introduction
- Wed, Jan 22
-
- Course Introduction & Landscape
Logistics, topics, grading, prerequisites, etc.
10 thousand foot view (Internet) to 100 feet view (programming) - Part 1 Slides / Part 2 Notebook
- Course Introduction & Landscape
- Fri, Jan 24
-
- Lab 1
Introduction to Wolfram Notebooks - Notebook
- Lab 1
Past & Present — Connecting the World
- Mon, Jan 27
-
- Course Introduction Contd.
- Part 2 Notebook
- Wed, Jan 29
-
- History and Map of Keywords
- Slides
- Fri, Jan 31
-
- No Lab
- Mon, Feb 3
-
- WiFi
- Slides
- Wed, Feb 5
-
- Cellular
- Slides
- Fri, Feb 7
-
- Lab 2
WiFi and Cellular - Notebook
- Lab 2
- Mon, Feb 10
-
- Internet (1/3)
Connectivity, Forwarding, and Routing - Slides
- Internet (1/3)
- Wed, Feb 12
-
- Internet (2/3)
HTTP and DNS - Slides
- Internet (2/3)
- Fri, Feb 14
-
- Lab 3
Internet and Graphs - Notebook
- Lab 3
- Mon, Feb 17
-
- Internet (3/3)
TCP and Layering - Slides
- Internet (3/3)
- Wed, Feb 19
-
- Client-Server;
Distribution and Streaming Part 1 - Slides contd. from Monday
- Client-Server;
- Fri, Feb 21
-
- Lab 4
Distribution and Streaming - Notebook
- Lab 4
- Mon, Feb 24
-
Client-Server;Distribution and Streaming- Slides
- Wed, Feb 26
-
- Social Networks
- Slides
- Fri, Feb 28
-
- Lab 5
Social Networks - Notebook
- Lab 5
- Mon, Mar 3
-
- File Systems
- Slides
- Wed, Mar 5
-
- Exam Review
- Study Guide
- Fri, Mar 7
-
- Exam 1
Intelligence & Implications
- Mon, Mar 10
-
- Introduction to Machine Intelligence
- Slides
- Wed, Mar 12
-
- Search Engines
- Slides
- Fri, Mar 14
-
- Lab 6
Search Engines - Notebook
- Lab 6
- Sat, Mar 15
- Spring Break Begins
- Sun, Mar 23
- Spring Break Ends
- Mon, Mar 24
- Wed, Mar 26
-
- Machine Learning (1/2): Introduction
- Notebook
- Fri, Mar 28
-
- Lab 7
Machine Learning - Notebook
- Lab 7
- Mon, Mar 31
-
- Machine Learning (2/2): Supervised and Unsupervised Learning
- Slides
- Wed, Apr 2
-
- Ethics, Privacy and Fairness
- Slides
- Fri, Apr 4
-
- Lab 8
Neural Networks and LLMs - Notebook
- Lab 8
- Mon, Apr 7
-
- Physical Security and Authentication
- Slides
- Wed, Apr 9
-
- Exam 2 Review
- Study Guide
- Fri, Apr 11
-
- Exam 2
Future
- Mon, Apr 14
-
- Sense-Compute-Communicate-Actuate I
- Notebook
- Wed, Apr 16
-
- Sense-Compute-Communicate-Actuate II
- Notebook
- Fri, Apr 18
-
- Lab 9
Sense-Compute-Communicate-Actuate
- Lab 9
- Mon, Apr 21
-
- Computer Vision
- Slides
- Wed, Apr 23
-
- Speech and Natural Language Processing
- Slides
- Fri, Apr 25
-
- Lab 10
Computer Vision - Notebook
- Lab 10
- Mon, Apr 28
-
- Augmented Reality/Virtual Reality
- Slides
- Wed, Apr 30
-
- Self-driving
- Slides
- Fri, May 2
-
- Lab 11
Working with Data - Notebook
- Lab 11
Final Week
- Mon, May 5
-
- Exam 3 Review
- Study Guide
- Wed, May 7
-
- Exam 3
Exam Information
The course has three midterm exams. There will NOT be any final exam.
Each exam will be 50 mins long. You are allowed 1 letter-size (8.5" x 11") handwritten cheatsheet (you may use both sides). The exam is closed book/notes, and calculators are not allowed.
Detailed information on logistics, format, and grading will be provided during exam review sessions.
Exam 1
Exam 1 will be on Mar 7. This exam will test concepts covered in the Past & Present module.
Exam 2
Exam 2 will be on April 11. This exam will test concepts covered in the Intelligence & Implications module.
Exam 3
Exam 3 will be on May 7. This exam will test concepts covered in the Future module.
Grading Information
Your final grade will be based on a weighted combination of the following:
- Classroom participation: 15% (6 absences allowed)
- Homework: 10%
- Weekly Labs (best 10 out of 11): 30%
- Three Midterm Exams: 3 x 15 = 45%
(Regrade policy: Correct mistakes and turn in for half of the points lost.)