Special Offer for WiBD Members
Net Academy is inviting a limited number of Women in Big Data members to high-quality, fifty-hour online training offerings on Big Data and Analytics. Members who successfully complete the courses will receive a certificate of completion.
Click here to get an individual promotion code.
You must be part of our Women in Big Data LinkedIn forum to register.
Click here for more detailed information about the training.
Levels: I=Introductory, INT=Intermediate, U=Undergrad, A=Advanced
General
Math
- Calculus (Khan Academy) -I-
- Multivariate Calculus (MIT) -U-
- Linear Algebra (MIT) -U-
Statistics
- Introduction to Probability & Data (Coursera, Duke) -I-
- Linear Regression & Modeling (Coursera, Duke) -I-
- Bayesian Statistics (Coursera, Duke) -A-
- Probabilistic System Analysis & Applied Probability (MIT) -U-
- Bayesian Statistics (UC Santa Cruz) -INT-
- CS109: Intro to Probability for Computer Scientists (Stanford) -I-
Python
- Intro to Python for Data Science (DataCamp) -I-
- Complete Python Bootcamp (Udemy) -I-
- Introduction of Comp Sci & Programming Using Python (edx) -I-
- Python Beyond the Basics - Object-Oriented Programming (Udemy) -A-
R
- R Programming (Coursera, JHU) -INT-
- Introduction to R for Data Science (edX) I-
Big Data & Cloud Computing
- Who’s Who in Big Data (WiBD) -INT-
- Cloud Systems and Infrastructure (Coursera, UIUC) -INT-
- Big Data and Applications in the Cloud (Coursera, UIUC) -A-
- Spark and Python for Big Data with PySpark (Udemy) -INT-
- Big Data Modeling and Management Systems (Coursera, UCSD) -INT-
- Big Data Integration and Processing (Coursera, UCSD) -INT-
- Intro to Big Data and MapReduce (Udacity, Cloudera) -I-
- Scalable Microservices with Kubernetes (Udacity, Google) -A-
SQL
- The SQL Tutorial for Data Analysis (Mode Analytics) -I-
- Managing Big Data with MySQL (Coursera, Duke) -I-
Machine Learning
- Introduction to Machine Learning (WiBD) -I-
- Machine Learning by Andrew Ng (Coursera) -INT-
- Stanford CS229 Machine Learning (Course Page), (Youtube, 2008) -INT-
- Berkeley CS 189 Introduction to Machine Learning (Berkeley) -A-
- Google Machine Learning Crash Course (Google) -I-
Deep Learning & Neural Network
- Lightweight Object Detectors: Overview (WiBD) -I-
- Neural Nets: Development Process (WiBD) -I-
- AI and Big Data Analytics (WiBD) -I-
- Neural Networks and Deep Learning by Andrew Ng (Coursera) -A-
- Convolutional Neural Networks by Andrew Ng (Coursera) -A-
- MIT 6.S191: Introduction to Deep Learning (MIT) -INT-
- CS231n: Convolutional Neural Networks for Visual Recognition (Youtube, Stanford) -A-
- CS224n: Natural Language Processing with Deep Learning (Youtube, Stanford) -A-
- MIT 6.S094: Deep Learning for Self-Driving Cars (Youtube, MIT) -A-
- Neural Network for Machine Learning (Coursera, U of Toronto) -INT-
- ai Courses (fast.ai) -INT-
- Stanford CS20SI - TensorFlow (Youtube, Stanford) -INT-
Computer Science
- MIT Introduction to Algorithms (MIT OCW) -U-
- Berkeley CS 61B Data Structures (Berkeley course website) INT-
- Database System Concepts & Design (Udacity, GIT) -INT-
- Stanford Database (Stanford Online) -I-
- Introduction to Operating System (Udacity, GIT) -A-
- Software Development Process (Udacity, GIT) -INT-
Experiment Design
- A/B Testing (Udacity) -INT-
Visualization
- Data Visualization and Communication with Tableau (Coursera, Duke) -INT-
- Data Visualization and D3.js (Udacity) -INT-
Time Series Analysis
- Time Series Forecasting (Udacity) -INT-
Python
Bash
Data Mining
- Stanford CS246 Mining of Massive Dataset (free book)
Statistics
- Applied Statistics by David Dalpiaz UIUC (UIUC, web textbook)
- Statistics in a Nutshell (Amazon)
- Penn State University Statistics Courses (PSU Online)
- Computer Age Statistical Inference (Stanford, free book)
Machine Learning
- The Elements of Statistical Learning (Stanford, free book)
- An Introduction to Statistical Learning (Stanford, free book)
- Pattern Recognition & Machine Learning (Amazon)
- Stanford CS229 Machine Learning Notes, Andrew Ng (Lecture Notes)
- Hands-on Machine Learning with Scikit-learn and TensorFlow (Amazon)
Deep Learning & Neural Network
- Deep Learning by Ian Goodfellow (free book)
Natural Language Processing
- Natural Language Processing with Python (free book)
Product Sense
Coding Practices
Data Science
- Analytics Vidhya (blog)
- R Bloggers (web)
- KDnuggets (blog)
- Kaggle official blog (blog)
- Dataquest (blog)
- Data Tau News (news)
Company Engineering / Data Science Blogs
Please note: These are courses recommended by your peers; they have NOT been verified by WiBD (unless specifically stated in the recommended course section).
We would love to hear from you!
Anybody else doing the Machine Learning Course by Andrew Ng on Coursera ? Would love to set up a slack group and work each week together to keep us on track. Please reply here.