Data Science is an ever-evolving field, and whether you are a beginner or looking to sharpen your skills, having the right resources can make a world of difference. This article aims to provide you with a comprehensive guide filled with valuable resources, thoughtfully categorized into different areas of focus. Let’s embark on this learning journey together!

Table of Contents

• One Month Plan
• Machine Learning
• Natural Language Processing
• Deep Learning
• Systems
• Analytics
• Reinforcement Learning
• Other Courses
• Interviews
• Bayesian
• Time series
• Quant
• More Lists

One Month Plan

If you’re feeling overwhelmed by the abundance of resources, here’s a structured one-month plan that can get you off the ground:

• Learn Python the hard way: Free Book
• Stanford Statistical Learning: Course Page or Coursera by Andrew Ng: Coursera, YouTube
• Ng’s Deep Learning Courses: Coursera
• Keras in 30 seconds: Link
• Stanford Database Course: Course

Machine Learning

Videos

• Stanford Statistical Learning: Course Page
• Coursera by Andrew Ng: Coursera, YouTube
• Stanford CS229: YouTube, Course Page
• Machine Learning Foundations: Coursera
• Machine Learning Techniques: YouTube
• CMU 701: Course Page

Textbooks

• Introduction to Statistical Learning: PDF
• Computer Age Statistical Inference: PDF
• The Elements of Statistical Learning: PDF
• Machine Learning Yearning: Website

Comments

The Statistical Learning course is a great introduction, and it’s free to earn a certificate. Coursera’s course by Andrew Ng is another popular choice, sufficient for most data science positions. For those seeking a deeper dive, consider CS229 or CS701, along with reading the Elements of Statistical Learning.

Natural Language Processing

Videos

• Stanford Basic NLP Course on Coursera: Videos
• CS224n NLP with Deep Learning: Course Web, Videos
• CMU – Neural Nets for NLP 2017: Course Web
• Deep Learning for Natural Language Processing: Course Web
• Sequence Models by Andrew Ng on Coursera: Coursera

Books

• Speech and Language Processing (3rd ed. draft): Book
• An Introduction to Information Retrieval: PDF
• Deep Learning Book: Book
• NLP by Jacob Eisenstein: Free Book Draft

Packages

• NLTK
• Stanford Packages

Deep Learning

Videos

• Ng’s Deep Learning Courses: Coursera
• Stanford CS231n: YouTube, Course Page
• MIT 6.S094: Deep Learning for Self-Driving Cars: YouTube
• Neural Networks for Machine Learning by Hinton: Coursera

Books

• Deep Learning by Ian Goodfellow: Book
• ArXiv for research updates: ArXiv

Systems

• Docker Mastery
• The Ultimate Hands-On Hadoop
• Spark and Python for Big Data with PySpark

Analytics

• Lean Analytics
• Data Science for Business
• Data Smart
• Storytelling with Data

Reinforcement Learning

Videos

• Udacity Course: Course
• UCL Course on RL by David Silver: Course Page
• CS 294: Deep Reinforcement Learning by UC Berkeley: Course Page

Books

• Reinforcement Learning: An Introduction (2nd Edition): PDF

Other Courses

• Recommender System by UMN
• Mining Massive Datasets (Free Book)
• Introduction to Algorithms (MIT)
• Database Course by Stanford
• How to Win a Data Science Competition
• How to finish a Data Challenge

Interviews

Lists with Solutions

• 111 Data Science Interview Questions Detailed Answers
• 40 Interview Questions Asked at Startups
• 100 Data Science Interview Questions and Answers (General)
• 21 Must-Know Data Science Interview Questions
• 45 Questions to Test on Basics of Deep Learning
• 30 Questions on Natural Language Processing
• Questions on Stackoverflow
• Compare two models

Without Solutions

• Over 100 Data Science Interview Questions
• 20 Questions to Detect Fake Data Scientists
• Questions on Glassdoor

Bayesian

Courses

• Bayesian Statistics: From Concept to Data Analysis
• Bayesian Methods for Machine Learning
• Statistical Rethinking

Books

• Bayesian Data Analysis, Third Edition
• Applied Predictive Modeling

Time Series

Courses

• Time Series Forecasting
• Topics in Mathematics with Applications in Finance (MIT)

Books

• Time Series Analysis and Its Applications

With LSTM

• LSTM Model
• Multivariate Time Series Forecasting

Quant

Books

• Heard on the Street
• A Practical Guide To Quantitative Finance Interviews

Courses

• Financial Markets with Robert Shiller (Yale)
• MAT (MIT)

More

• Computer Science Courses with Video Lectures
• The Open Source Data Science Masters

Troubleshooting

As you navigate through these resources, you may encounter challenges such as accessing links, difficulties with course content, or needing further clarification on specific topics. Here are some troubleshooting tips:

• Ensure that your internet connection is stable to avoid interruptions while accessing online courses.
• If a video does not play, try refreshing the page or switching to a different browser.
• For issues with understanding course content, consider joining forums or discussion groups related to the course.
• Taking notes while watching videos can greatly enhance your retention of the material.

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Conclusion

In conclusion, whether you are just getting started with data science or looking to enhance your existing knowledge, the resources listed here provide a well-rounded foundation. Dive in, stay curious, and let your learning journey unfold!