From PDE to Machine Learning From Academia to
- Slides: 12
From PDE to Machine Learning; From Academia to Industry KO-SHIN CHEN UNIVERSITY OF CONNECTICUT
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
Online Courses and Resources Courses § Coursera: https: //www. coursera. org/ (verified certificate) o Single course/ Specialization (series of courses + capstone project) § ed. X: 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 § You. Tube
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 (Mat. Lab) § Inferential Statistics Fundamentals of Computing Java Programming: Object-Oriented Design of Data Structures
Learning Path of ML Machine Learning Background Knowledge Videos § Machine Learning Foundations by Hsuan-Tien Lin (You. Tube) § Machine Learning Techniques by Hsuan-Tien Lin (You. Tube) § MIT 6. S 094: 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
Learning Path of ML Techniques Online Courses § Functional Programming in Scala Specialization (Coursera) § Complete Guide to Tensor. Flow 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)
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 Ph. D § 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
Resume Styles: academic positions v. s. industry jobs Additional Elements § Git. Hub: sample code/ projects § Linkedin: build network with recruiters
Sits for Job Search Indeed: https: //www. indeed. com/ Monster: https: //www. monster. com/ § See what your resume looks like in application tracking system Angel. List (startup): https: //angel. co/ Flexjobs (remote jobs): https: //www. flexjobs. com/
Prepare for an Interview Books § Cracking the Coding Interview by Gayle Laakmann Mc. Dowell § Cracking the PM Interview by Gayle Laakmann Mc. Dowell Coding Practice § Leet. Code: https: //leetcode. com/ § Hacker. Rank: 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
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
Thank you!
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- Pac learning model in machine learning
- Pac learning model in machine learning
- Inductive and analytical learning
- Difference between inductive and analytical learning
- Instance based learning in machine learning
- Inductive learning machine learning
- First order rule learning in machine learning
- Lazy learning vs eager learning
- Deep learning vs machine learning
- Cuadro comparativo e-learning b-learning m-learning
- Pde solutions