EECS16A, Designing Information Devices and Systems I
Spring 2021
Scheduling Updates
1/18/2021: Zoom links will be posted on Piazza! You can access the Piazza page for this course here.
Schedule
Please note that Youtube videos will require that you are signed into a berkeley.edu account. Otherwise, you'll see some indication of the video being private. The schedule below is subject to change; for deviations from the schedule, see above.
Note: Due to Zoom's password length constraints, the password for cloud recordings for discussion will be eecs16a! .
(Please scroll horizontally if you're viewing this on your phone.)
Week  Date  Lecture Topic  Section  Lab  Homework 

0

01/19 Tu 
Overview, Introduction to Imaging
Slides Recording Link (Note 0) 
Section 0A (Mon)
No Section 
No Lab

Homework 00 (Due 01/22 Fr) Prob PDF Sol PDF Self Grade 
01/21 Th 
Systems of Linear Equations and Gaussian Elimination
Slides Recording Link Recording Q&A (Note 1A) (Note 1B) 
Section 0B (Wed)
No Section 

1

01/26 Tu 
More Gaussian Elimination, Matrix Vector Multiplication
Slides Recording Link Recording Q&A (Note 2A) (Note 2B) 
Section 1A (Mon)
Jamboard Link Miyuki's Recording Miyuki's Notes Bob's Recording Bob's Notes Checkoff 1A/1B Prob PDF Ans PDF 
Python Bootcamp
Presentation Datahub Link Sols Datahub Link 
Homework 01 (Due 01/29 Fr) Prob PDF Sol PDF Self Grade Practice Sets Practice Set 0 Practice Set 0 Notes Practice Set 0 Solutions Practice Set 1 Practice Set 1 Notes Practice Set 1 Solutions 
01/28 Th 
Introduction to Proofs, Span, Linear Dependence and Independence
Slides Recording Link Recording Q&A (Note 3) (Note 4) 
Section 1B (Wed)
Jamboard Link Miyuki's Recording Miyuki's Notes Bob's Recording Bob's Notes Checkoff 1A/1B Prob PDF Ans PDF 

2

02/02 Tu 
Linear Transformations, Matrix matrix multiplication
Slides Recording Link Recording Q&A (Note 5) 
Section 2A (Mon)
Jamboard Link Miyuki's Recording Miyuki's Notes Bob's Recording Bob's Notes Checkoff 2A/2B Prob PDF iPython Datahub Link Ans PDF 
Imaging I
Presentation Hardware (Datahub) Software (Datahub) 
Homework 02 (Due 02/05 Fr) Prob PDF iPython .zip Prob Datahub Link Sol PDF iPython Sol Sol Datahub Link Self Grade Practice Sets Practice Set 2 Practice Set 2 Notes Practice Set 2 Solutions 
02/04 Th 
Inversion
Slides Recording Link Recording Q&A (Note 6) 
Section 2B (Wed)
Jamboard Link Miyuki's Recording Miyuki's Notes Bob's Recording Bob's Notes Checkoff 2A/2B Prob PDF iPython Datahub Link Ans PDF 

3

02/09 Tu 
Vector Spaces: Null spaces and Columnspaces
Slides Recording Link Recording Q&A (Note 7) (Note 8) 
Section 3A (Mon)
Jamboard Link Miyuki's Recording Miyuki's Notes Bob's Recording Bob's Notes Checkoff 3A/3B Prob PDF iPython Datahub Link Ans PDF 
Imaging II
Presentation Datahub Link 
Homework 03 (Due 02/12 Fr) Prob PDF iPython .zip Prob Datahub Link Sol PDF iPython Sol Sol Datahub Link Self Grade Practice Sets Practice Set 3 Practice Set 3 Notes Practice Set 3 Solutions 
02/11 Th 
Page Rank, Eigenvalues and Eigenspaces
Slides Recording Link Recording Q&A (Note 9) 
Section 3B (Wed)
Jamboard Link Miyuki's Recording Miyuki's Notes Bob's Recording Bob's Notes Checkoff 3A/3B Prob PDF Ans PDF 

4

02/16 Tu 
Eigenvalues and Eigenspaces
Slides Recording Link Recording Q&A (Note 9) 
Section 4A (Mon)
No Section 
No Lab

Homework 04 (Due 02/19 Fr) Prob PDF iPython .zip Prob Datahub Link Sol PDF iPython Sol Sol Datahub Link Self Grade Practice Sets Practice Set 4 Practice Set 4 Notes Practice Set 4 Solutions 
02/18 Th 
Change of Basis, Diagonalization
Slides Recording Link Recording Q&A (Note 10) 
Section 4B (Wed)
Jamboard Link Miyuki's Recording Miyuki's Notes Bob's Recording Bob's Notes Checkoff 4B Prob PDF iPython Datahub Link Ans PDF 

5

02/23 Tu 
Intro to Circuit Analysis
Slides Recording Link Recording Q&A (Note 11) 
Section 5A (Mon)
Jamboard Link Miyuki's Recording Miyuki's Notes Bob's Recording Bob's Notes Prob PDF Ans PDF 
Imaging III
Presentation Datahub Link 
Homework 05 (Due 02/26 Fr) Prob PDF iPython .zip Prob Datahub Link Sol PDF iPython Sol Sol Datahub Link Self Grade Practice Sets Practice Set 5 Practice Set 5 Notes Practice Set 5 Solutions 
02/25 Th 
Introduction to Modeling with Circuit Elements
Slides Recording Link Recording Q&A (Note 12) 
Section 5B (Wed)
Jamboard Link Miyuki's Recording Miyuki's Notes Bob's Recording Bob's Notes Prob PDF Ans PDF 

6
MT1, Mar. 1, 79 PM PT 
03/02 Tu  Power and Voltage/Current Measurement 
Section 6A (Mon)

Buffer (Imaging I/II/III)

Homework 6 (Due 03/05 Fr) Practice Sets Practice Set 6 Practice Set 6 Notes Practice Set 6 Solutions 
03/04 Th  2D Touchscreen 
Section 6B (Wed)


7

03/09 Tu  Superposition and Equivalence 
Section 7A (Mon)

Touch I (+ Breadboarding Bootcamp)

Homework 7 (Due 03/12 Fr) Practice Sets Practice Set 7 Practice Set 7 Notes Practice Set 7 Solutions 
03/11 Th  Introduction to Capacitive Touchscreen 
Section 7B (Wed)


8

03/16 Tu  Capacitance modeling and measurement 
Section 8A (Mon)

Touch II

Homework 8 (Due 03/19 Fr) Practice Sets Practice Set 8 Practice Set 8 Notes Practice Set 8 Solutions 
03/18 Th  Opamps and Negative Feedback 
Section 8B (Wed)


9

03/30 Tu  Opamp Circuit Analysis 
Section 9A (Mon)

Touch III

Homework 9 (Due 04/02 Fr) Practice Sets Practice Set 9 Practice Set 9 Notes Practice Set 9 Solutions 
04/01 Th  Design Procedure and Design Examples 
Section 9B (Wed)


10

04/06 Tu  Design Examples 
Section 10A (Mon)

Buffer (Touch I/II/III)

Homework 10 (Due 04/09 Fr) 
04/08 Th  Introduction to the locationing (GPS) lab. ML problem 1: Classification 
Section 10B (Wed)


11
MT2, Apr. 12, 79 PM PT 
04/13 Tu  ML problem 2: Estimating the propagation delays 
Section 11A (Mon)

No Lab

Homework 11 (Due 04/16 Fr) Practice Sets Practice Set 10 Practice Set 10 Notes Practice Set 10 Solutions 
04/15 Th  ML problem 3: Fitting data using Least Squares 
Section 11B (Wed)


12

04/20 Tu  ML problem 4: Prediction. Least squares contiued 
Section 12A (Mon)

APS I

Homework 12 (Due 04/23 Fr) Practice Sets Practice Set 11 Practice Set 11 Notes Practice Set 11 Solutions 
04/22 Th  Greedy Algorithms for Machine Learning 
Section 12B (Wed)


13

04/27 Tu  Machine Learning continued 
Section 13A (Mon)

APS II

Homework 13 (Due 04/30 Fr) 
04/29 Th  More Machine Learning 
Section 13B (Wed)


14
Final, May 12, 11:30 AM  2:30 PM PT 
05/04 Tu  RRR Week 
Section 14A (Mon)
No Section 
APS Buffer


05/06 Th  RRR Week 
Section 14B (Wed)
No Section 
Notes
Grey notes are *still relevant material* for the course! They simply have not yet been covered in lecture. Blue notes have been covered in lecture. Notes with an [updated] tag to their left have been changed since last semester's iteration. Be aware that the unupdated notes are subject to change. Note 0  Introduction
 Note 1A  Systems of Linear Equations
 Note 1B  Gaussian Elimination
 Note 2A  Matrices and Vectors
 Note 2B  Matrix Multiplication
 Note 3  Linear Independence and Span
 Note 4  Mathematical Thinking and Derivation
 Note 5  Water Reservoirs, Pumps and Matrix Multiplication
 Note 6  Matrix Inversion
 Note 7  Vector Spaces
 Note 8  Matrix Subspaces
 Note 9  Eigenvalues and Eigenvectors
 Note 10  Change of Basis
 Note 11  Introduction to Circuit analysis
 Note 12  Voltage Dividers and Resistors
 Note 13  Resistive Touchscreen and Power
 Note 14  More Resistive Touchscreen
 Note 15  Superposition and Equivalence
 Note 16  Capacitors
 Note 17  Capacitive Touchscreen
 Note 17B  Charge Sharing
 Note 17C  Comparators
 Note 18  OpAmps in Negative Feedback
 Note 19  More OpAmp Topologies
 Note 20  OpAmp Current Source and Circuit Design
 Note 21  Inner Products and GPS
 Note 22  Trilateration and Correlation
 Note 23  Least Squares
 Note 24  Orthogonal Matching Pursuit
 Note 25  More Trilateration
Calendars
Office hours and HW Party are held here.
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NOTE (1/18/21): Calendar events for this semester are still being added in. Please be patient if you see missing events. Thanks!
Discussion Schedule
Please note the important information below the table. The set of ASEs assisting with a given discussion (if any) is given by the bulleted list.
Discussion Schedule  
Time (Mon/Wed)  Lecture Style  Individual Worktime  Group Section  
8am9am  Xiaosheng


9am10am  
10am11am  Varun [PRIOR LINEAR ALGEBRA EXPERIENCE]


11am12pm  Miyuki [RECORDED] 

12pm1pm  David [TRANSFER]


1pm2pm  David

Lily


2pm3pm  Bob [RECORDED] 
Austin [FRESHMAN]


3pm4pm  Ashwin


4pm5pm  Dahlia [CS SCHOLARS]


5pm6pm  Dylan

Note: Monday and Wednesday discussion sections cover different material, and you are very strongly encouraged to go to a discussion both days. Scroll horizontally to view entire table, and see below for critical information on how to read the table.
To account for different learning styles, there will be 3 different styles of discussion sections.
 The first set of sections are “Group Sections" (blue) . These discussion sections will be staffed with a TA and many ASEs, and students will be given a chance to work with each other in breakout rooms.
 The second type of sections are "Individual Worktime" (green) , which are more oriented toward individual work and are intended for students who prefer working solo and not in groups. Here, the TA will give you time to work on the problem on your own and then discuss the answer.
 The last type of section (similar to the second type) is "Lecture Style" (purple) . There may be slightly less time for individual work on the problems in the Lecture Style sessions, but TAs will be there to answer questions in all sessions.
Furthermore note the following; despite the bold labels in some sections, all sections are open to all. However, to facilitate similar groups of students getting to know each other, we have designated sections according to categories. Freshman section or Freshman/Sophomore sections are intended for these specific years of students. Transfer sections are intended for Transfer students. The Linear Algebra experience section is intended for upper division students who might have some prior linear algebra experience. Again, all sections are open to all.
Resources
Piazza (Ask Questions Here)
Homework Practice Problems
Textbook: Condensed Note Content Summaries and Practice Problem Solutions
This book consists of condensed sets of notes that summarize the important material from the course notes, as well as detailed solutions for the online Practice Problems! Here's the entire book and the Table of Contents. Individual chapters of the book (notes and solutions by practice set) can be found here (the links aren't perfect, you may need to scroll a tiny bit down for some chapters). A couple brief comments on using this resource:
 I recommend skimming the Introductory Chapter and the Conventions Chapter. These will provide some useful tips to keep in mind.
 Each chapter has a Relevant Information section and a Problems section. The first contains a (generally complete) summary of the corresponding content from the notes. The second contains the detailed solutions mentioned above.
 This is a new resource, and may well have errors or areas to improve in; if you spot something wrong and would like to mention it, or have feedback of any kind, please submit a feedback ticket.
Technology Needs (STEP)
Student Technology Equity Program (STEP). STEP provides laptops and other technologies for free and is for undergraduate, graduate, and professional students. It requires just a simple online application form. For details, see here.
Recommended Texts
 EE16A's Guide to the Recommended Texts
 ELECTRONICS Reader (50MB) by Ali M. Niknejad, or the smaller file without links (5MB)
 Intoduction to Linear Algebra by Gilbert Strang, 5th Ed.
 Schaum's Outlines of Linear Algebra, 5th ed. by Seymour Lipschutz and Marc Lipson. Free if login from the university network. Also see roaming passports.
 Schaum's Outline of Electric Circuits, 7th ed. by Mahmood Nahvi and Joseph A. Edminister. (instructions to login to the university network from home here )
Circuit Cookbooks
 Recipe: Nodal Analysis!
 Recipe: Charge Sharing!
 ChargeSharing Algorithm (Sp20)
 Recipe: Thevenin and Norton Equivalents! (INCOMPLETE)
 Recipe: Design Topologies!
Extra Resources
 StepByStep Gaussian Elimination by Andi Gu, a former student. Has at least one very minor bug regarding labeling of row operations.
 studEE16A (may need to load each page twice to view the LaTeX)
 Fun with Stacked Caps
 EECS16A Lab Equipment Guide
 Review of Past Proofs
 Fall 2020 Discussion Checkoffs: Questions and Answers
Setting up HowTo's
Past Exams
Past exams vary in scope from semester to semester, and may include topics that are not in scope for the current semester or module. Unavailable exams are indicated by N/A. Inscope topics for the current semester will be posted on Piazza about a week before the corresponding exam.Semester  Midterm 1  Midterm 2  Final 

fa20  pdf, sol  pdf, sol  pdf, sol 
su20  pdf, sol  pdf, sol  pdf, sol 
sp20  pdf, sol  pdf, sol  pdf, sol 
fa19  pdf, sol  pdf, sol  pdf, sol 
sp19  pdf, sol  pdf, sol  pdf, sol 
fa18  pdf, sol  pdf, sol  pdf, sol 
sp18  pdf, sol  pdf, sol  pdf, sol 
fa17  pdf, sol  pdf, sol  pdf, sol 
su17  pdf, sol  pdf, sol  N/A 
sp17  pdf, sol  pdf, sol  N/A 
fa16  pdf, sol  pdf, sol  pdf, sol 
sp16  pdf, sol  pdf, sol  pdf, sol 
fa15  pdf, sol  pdf, sol  pdf, sol 
sp15  pdf, sol  pdf, sol  pdf, sol 
Simulations and Demos
This is a running list of simulations and demos that have been created in recent semesters (in rough order of appearance).Practice Sets: Links to Notes and Solutions
It is very strongly recommend that you try the problems themselves here before looking at the solutions below. The links for solutions are not perfect, so you may need to scroll to the bottom of the linked page to find them. Give feedback here.
Course Staff
Please add berkeley.edu to the end of all emails!Instructor
I'm a professor in Electrical Engineering and Computer Sciences, and I work on research on Computational Microscopy, in which we design imaging systems that use physics/optics hardware and computational software together to do things that neither could do alone. Your cell phone camera probably has a lot of great examples of computational imaging, like portrait mode, HDR, and image bursts, and we'll learn a bit about imaging in this course! I look forward to working with you all this spring, even if only via Zoom.
waller@
GSIs
I'm a thirdyear EECS major currently conducting research in power electronics. My favorite part of 16A is the circuits module: I find the creative aspect of circuit design to be quite rewarding, and the handson lab work is super fun. Outside of academics, I love outdoor adventures (particularly aquatic ones), classical music, and cooking.
Head / Lab
she/her/hers
amandajackson@
Hi! My name is Anika. I am a 3rd year studying Industrial Engineering and Operations Research (IEOR for short) which is all about optimization and efficiency (i.e. making the world as lazy as I am)! This is my fifth semester on course staff for EECS 16A. I love this class because it helps bring fundamental concepts to life through an application focus. Outside of academics, I love to spend time with friends and watch netflix (always looking for good recommendations!) I am also a dancer and enjoy karaokeing disney songs. I look forward to this semester and I hope to help make this class a great experience for each and every one of you. Welcome to EECS 16A!
Head
she/her/hers
eecs16a@, anikar@
Hey there! I'm a second year EECS major currently involved in research in computational imaging, and this is my fourth semester on course staff. In my free time I love cooking, knitting, and walking around Berkeley. I loved taking 16A because it teaches how to use the concepts of linear algebra and circuit analysis as tools to apply to real problems, and I hope you enjoy the course as much as I did! I'm excited to get to know you this semester :)
HW / Admin / Discussion
she/her/hers
eecs16a.hw@, dahliasaba@
Hi! I'm Raghav, a junior in the EECS major. I am really interested in Computer Architecture, Machine Learning, and Quantum Computing (so far :). 16A is one of the best classes I've taken at Berkeley so far because of the unique perspective it gives one on solving real world problems with the simplicity of linear algebra. I'm very passionate about aviation, technology, soccer and F1. I love traveling, hiking and endurance running and cycling. Oh and I thoroughly enjoy talking to people, so feel free to hit me up!
Head Lab
he/him/his
raghav.tech13@
I'm a third year EECS major interested in embedded systems and aerospace. I like 16A because it provides a foundation in linear algebra and circuits with fun and interesting labs. Outside of school I enjoy playing tennis, video games, and hiking.
Head Lab
he/him/his
eecs16a.lab@, vidishgupta@
Hi everyone! I'm a second year EECS student. I'm excited to work on the 16A software team this year to make sure the class runs smoothly for you all. On campus I participate in microrobotics research, and in my free time I enjoy running!
Software / Dis
he/him/his
austinpatel@
Hi! I'm a 3rd year CS + Stats Major interested in all things Robotics and AI. In my free time, I enjoy playing squash, discussing politics, and ruining family photos. Looking forward to another semester at Zoom University!
Software
he/him/his
mohsin.sarwari@
Hello! I’m a sophomore studying Computer Science as an excuse to start the robot uprising. Currently, I’m researching how to teach robots to walk upright and push blocks on a table with machine learning (read: linear algebra). When I get frustrated with their progress, I watch Korean movies, write about philosophy, appreciate wordplay in books and puzzles, and reminisce about how cool least squares is.
Dis
he/him/his
adreddy@
Hi all! I'm a third year EECS major and I am a discussion TA this semester. I'm interested in digital circuit design, computer architecture, and firmware programming. My favorite nonEECS related pastimes are playing video games, eating, and running.
Dis
he/him/his
dylanbrater326@
Hi folks! I'm Lily, a senior studying EECS. In my spare time, I do research at CLTC and Haas, read interesting CS papers, and search for the most delicious way to cook cremini mushrooms. 16A was my favorite class as a freshman, and I look forward to helping make discussion fun and informative this semester!
Dis
she/her/hers
lbhattacharjee@
Salutations! I'm Aster, a thirdyear double majoring in Computer Science & Classical Languages (Latin and Greek). In my free time, I like practicing wushu (martial arts), reading novels, watching dramas, and writing stories :) My most recent obsession is MDZS/The Untamed. Feel free to talk to me any time or send me your favorite book recs!
Lab
asterguan@
My name is Dixun and I'm a mechanical engineering major from Toronto, Ontario, Canada, North America, Earth. I'm a die hard Toronto Maple Leafs fan and I also like playing and losing chess games, severely undercooking my steaks, losing money on put options, and jogging 1 mile once a week for exercise.
Lab
he/him/his
dixuncui@
Hello there! I'm a second year studying EECS and I'm really interested in machine learning, signal processing, and theoretical computer science. I'm currently doing research about applications of machine learning in education. In my free time I enjoy running, board games, exploring theories behind the meaning of life, and slaying noobs in Minecraft. I hope EECS 16A gives you infinite power with knowledge, and that you have a great semester!
Lab
he/him/his
fredwang@
Hi, I’m a 3rd year EECS major and I’m interested in the applications of machine learning and neural networks in autonomous driving and quantitative finance. Having grown up in Abu Dhabi, I love cold places. Talk to me about the IPL, cricket in general, and any of my academic interests. I wish you a great semester ahead!
Lab
he/him/his
rohansood@
Hey everyone! I'm a fourth year studying Bioengineering and EECS. On campus, I'm involved with the Society of Women Engineers and the Biomedical Engineering Society. In my free time, I love to bake, read, work out (although this happens very infrequently at this point), and photoshop my friends onto memes. Looking forward to a great semester!
Lab
she/her/hers
teresayang@
Hello! I am a senior in EECS. My favourite part of 16A were the labs, so I hope you will enjoy them too! My research involves developing a model to predict wildfire ignitions due to electric grid infrastructure in California. In my spare time I enjoy tennis, drinking tea and (recently) doing DIY crafts during shelterinplace.
Content / Lab
she/her/hers
meghana.bharadwaj@
Hi my name is Miyuki and I am a 5th year Masters student studying Mechanical Engineering. My technical interests include mechanical design and mechatronics, generally I enjoy any activity where I get to make stuff.
Content / Dis
she/her/hers
m.weldon@
I am a junior, majoring in Physics, Computer Science, and Applied Mathematics. My primary technical interests and areas of research activity are in Condensed Matter Physics and Quantum Information theory. I am particularly interested in the application of Quantum algorithms to Optimization and Machine learning problems. Outside academia, I participate in British parliamentary debate with the Debate Society of Berkeley. My favourite things to do in Berkeley in my spare time are to go on long bike rides and to hike the fire trails. I think that EECS16A is a uniquely foundational class, as it teaches immensely useful fundamental ideas in linear systems theory that are used virtually everywhere in the physical sciences and in engineering, at every level of complexity. I particularly enjoyed that the class exemplifies how a small but powerful set of mathematical tools and hardware abstractions can be used to design notably sophisticated systems.
Content / Dis
he/him/his
varunmenon@
I'm a 3rd year grad student working on electrical links. I did my undergrad here at Berkeley and actually took EE16A the first time it was offered. The 16AB series were some of my favorite classes during undergrad and inspired me to study circuits. In my spare time, I enjoy biking, ballroom dance, arranging music, and cooking.
Content / Dis
he/him/his
bob.linchuan@
David is a PhD student in EECS, and he works in the area of computational imaging for optical and electron microscopy. He hopes to interact with young minds when teaching 16A, and hopes that he has a couple of more friends when the semester is over.
Dis
david.ren@
I am a physics and electrical engineering PhD student who conducts research in Computational physics and atomic modeling. I really enjoy studying quantum physics, but when I’m not working I like soccer, hiking, surfing, climbing, and anything really that’s gets you moving and filled with adrenaline!
Content
he/him/his
jtreichanadter@
I'm a PhD student in EECS working on light detection and ranging (LiDAR) systems and optical beam steering devices. I'm broadly interested in the area of silicon photonics and microelectromechanical systems (MEMS). In my spare time I enjoy traveling, running, and cooking.
Content / Dis
he/him/his
xiaosheng_zhang@
About
EECS 16AB Course Coverage
EECS16AB was specially designed to ramp students up to prepare for courses in machine learning and design and are important classes to set the stage for the rest of your time in the department. A rough breakdown of the content in the classes is as follows:
16A:
Module 1: Introduction to systems and linear algebra
Module 2: Introduction to design and circuit analysis
Module 3: Introduction to machine learning
16B:
Module 1: Differential equations and advanced circuit design
Module 2: Introduction to robotics and control
Module 3: Introduction to unsupervised machine learning and classification
FAQ
Q1: Should I take EECS16A my first semester at Cal?
A1: If you have taken an AP calculus class, then the answer is yes! EECS16A has no prerequisites other than calculus and is designed with freshmen and incoming transfer students in mind. It is designed to be taken alongside 61A. Furthermore, we reserve seats for freshmen and incoming transfer students in the class, so you are essentially guaranteed a spot in the class your first year. It will be harder to get into the class as an upperclassman.
Q2: Should I take EECS 16A and EECS 16B before or after CS 70?
A2: EECS16A and 16B were specifically designed to help ease the transition to CS70 for incoming students. These classes provide an introduction to proofs and the kind of mathematical thinking that is very useful in a class like CS70. We recommend you take 16AB before taking CS70, this should help you have an easier time in CS 70.
Q3: Should I take MATH 54 before taking EECS16A?
A3: EECS 16A is designed to be taken without any prerequisites, so there is no need to take MATH 54 before EECS 16A. EECS 16AB teaches linear algebra with the intent of preparing you for courses like EECS 127 (Optimization) and EECS 189 (Machine Learning) and provides engineering and machine learning examples and applications for linear algebra. EECS 16AB also uses Jupyter notebooks and python so you can better connect linear algebra and computation.
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