From PDE to Machine Learning; From Academia to
Description: From PDE to Machine Learning; From Academia to Industry Ko-Shin Chen University of Connecticut Outline Background and Motivation Building Skills Online coursesresources Bootcamps Looking for Industry Jobs Resume Job search sites All About
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slide1. From PDE to Machine Learning; From Academia to Industry Ko-Shin Chen
University of Connecticut<br>
slide2. Outline Background and Motivation
Building Skills
Online courses/resources
Bootcamps
Looking for Industry Jobs
Resume
Job search sites
All About Interview
Preparation resources
Procedures and experiences<br>
slide3. Online Courses and Resources Courses
Coursera: https://www.coursera.org/ (verified certificate)
Single course/ Specialization (series of courses + capstone project)
edX: https://www.edx.org/ (verified certificate)
Udemy: https://www.udemy.com/
Online degrees
UIUC CS/DS (via Coursera)
Georgia Tech OMS CS
Free resources
MIT Open Course: https://ocw.mit.edu/index.htm
YouTube<br>
slide4. Learning Path of ML Basic Coding Skills (Coursera)
An Introduction to Interactive Programming in Python 1,2
Principles of Computing 1,2
Algorithmic Thinking 1,2
Object Oriented Programming in Java
Data structures: Measuring and Optimizing Performance
Advanced Data Structures in Java
R Programming
Getting and Cleaning Data (R)
Machine Learning by Andrew Ng (MatLab)
Inferential Statistics Fundamentals of Computing Java Programming: Object-Oriented Design of Data
Structures<br>
slide5. Learning Path of ML Machine Learning Background Knowledge
Videos
Machine Learning Foundations by Hsuan-Tien Lin (YouTube)
Machine Learning Techniques by Hsuan-Tien Lin (YouTube)
MIT 6.S094: Deep Learning for Self-Driving Cars (https://selfdrivingcars.mit.edu/)
Books
Numerical Optimization by Jorge Nocedal and Stephen J. Wright
The Elements of Statistical Learning by Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie<br>
slide6. Learning Path of ML Techniques
Online Courses
Functional Programming in Scala Specialization (Coursera)
Complete Guide to TensorFlow for Deep Learning with Python (Udemy)
SQL Advanced (Udemy)
UConn: CSE 5304-001 High-Performance Computing
Conferences
Neural Information Processing Systems (NIPS)
Knowledge Discovery and Data Mining (SIGKDD)
International Conference on Machine Learning (ICML)<br>
slide7. Bootcamps (Data Science) Insight
Data Science/ Data Engineering/ Health Data/ AI/ Data PM (new)
Postdoctoral training
Locations: Silicon Valley, New York, Boston, Seattle, and Remote
7 weeks
The Data Incubator (Data Science Fellowship)
Master and PhD
Locations: New York City, San Francisco Bay Area, Seattle, Boston, and Washington DC
8 weeks
Must intend to get hired full-time after the program<br>
slide8. Resume Styles: academic positions v.s. industry jobs
Additional Elements
GitHub: sample code/ projects
Linkedin: build network with recruiters<br>
slide9. Sits for Job Search Indeed: https://www.indeed.com/
Monster: https://www.monster.com/
See what your resume looks like in application tracking system
AngelList (startup): https://angel.co/
Flexjobs (remote jobs): https://www.flexjobs.com/<br>
slide10. Prepare for an Interview Books
Cracking the Coding Interview by Gayle Laakmann McDowell
Cracking the PM Interview by Gayle Laakmann McDowell
Coding Practice
LeetCode: https://leetcode.com/
HackerRank: https://www.hackerrank.com/
Pramp: https://www.pramp.com/
Company Research
Culture, mission, and values
Clients, products, and services
The team and person interviewing you<br>
slide11. The Interview Process HR phone screen
Company and job description
Resume and past experiences
Technical phone interview
Background knowledge
Live coding without IDE
CEO/ team leader phone interview (startup)
Behavioral questions
Details in projects and skills
Onsite interview<br>
slide12. Thank you!<br>
University of Connecticut<br>
slide2. Outline Background and Motivation
Building Skills
Online courses/resources
Bootcamps
Looking for Industry Jobs
Resume
Job search sites
All About Interview
Preparation resources
Procedures and experiences<br>
slide3. Online Courses and Resources Courses
Coursera: https://www.coursera.org/ (verified certificate)
Single course/ Specialization (series of courses + capstone project)
edX: https://www.edx.org/ (verified certificate)
Udemy: https://www.udemy.com/
Online degrees
UIUC CS/DS (via Coursera)
Georgia Tech OMS CS
Free resources
MIT Open Course: https://ocw.mit.edu/index.htm
YouTube<br>
slide4. Learning Path of ML Basic Coding Skills (Coursera)
An Introduction to Interactive Programming in Python 1,2
Principles of Computing 1,2
Algorithmic Thinking 1,2
Object Oriented Programming in Java
Data structures: Measuring and Optimizing Performance
Advanced Data Structures in Java
R Programming
Getting and Cleaning Data (R)
Machine Learning by Andrew Ng (MatLab)
Inferential Statistics Fundamentals of Computing Java Programming: Object-Oriented Design of Data
Structures<br>
slide5. Learning Path of ML Machine Learning Background Knowledge
Videos
Machine Learning Foundations by Hsuan-Tien Lin (YouTube)
Machine Learning Techniques by Hsuan-Tien Lin (YouTube)
MIT 6.S094: Deep Learning for Self-Driving Cars (https://selfdrivingcars.mit.edu/)
Books
Numerical Optimization by Jorge Nocedal and Stephen J. Wright
The Elements of Statistical Learning by Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie<br>
slide6. Learning Path of ML Techniques
Online Courses
Functional Programming in Scala Specialization (Coursera)
Complete Guide to TensorFlow for Deep Learning with Python (Udemy)
SQL Advanced (Udemy)
UConn: CSE 5304-001 High-Performance Computing
Conferences
Neural Information Processing Systems (NIPS)
Knowledge Discovery and Data Mining (SIGKDD)
International Conference on Machine Learning (ICML)<br>
slide7. Bootcamps (Data Science) Insight
Data Science/ Data Engineering/ Health Data/ AI/ Data PM (new)
Postdoctoral training
Locations: Silicon Valley, New York, Boston, Seattle, and Remote
7 weeks
The Data Incubator (Data Science Fellowship)
Master and PhD
Locations: New York City, San Francisco Bay Area, Seattle, Boston, and Washington DC
8 weeks
Must intend to get hired full-time after the program<br>
slide8. Resume Styles: academic positions v.s. industry jobs
Additional Elements
GitHub: sample code/ projects
Linkedin: build network with recruiters<br>
slide9. Sits for Job Search Indeed: https://www.indeed.com/
Monster: https://www.monster.com/
See what your resume looks like in application tracking system
AngelList (startup): https://angel.co/
Flexjobs (remote jobs): https://www.flexjobs.com/<br>
slide10. Prepare for an Interview Books
Cracking the Coding Interview by Gayle Laakmann McDowell
Cracking the PM Interview by Gayle Laakmann McDowell
Coding Practice
LeetCode: https://leetcode.com/
HackerRank: https://www.hackerrank.com/
Pramp: https://www.pramp.com/
Company Research
Culture, mission, and values
Clients, products, and services
The team and person interviewing you<br>
slide11. The Interview Process HR phone screen
Company and job description
Resume and past experiences
Technical phone interview
Background knowledge
Live coding without IDE
CEO/ team leader phone interview (startup)
Behavioral questions
Details in projects and skills
Onsite interview<br>
slide12. Thank you!<br>