ABCDEFGHIJKLMNOPQRSTUVWXYZ
1
TitleTopicDescriptionLanguageModalityLevel of DifficultyLinkOther
2
Introduction to Computer Science and Programming Using PythonIntro to Computer Science Using PythonComputer Science is at the heart of all programming. It's often beneficial in your career as a data scientist to understand CS principals so you can communicate with your engineers and understand the limitations of algorithms and your code.PythonOnline EducationModeratehttps://bit.ly/2IvLZd4This course can be audited for free or you can pay 75 for the certificate.
3
Complete Python BootcampIntroduction to PythonA beginners guide to Python. Before you can become a data scientist you need to know the language you will be using. This course offers a complete overview of programming in Python. Loops and Functions will become increasingly important as you become more advanced.PythonOnline EducationBeginnerhttps://bit.ly/2UlHqXvThe link provided should allow you to get the course for 11
4
Python for Data Science and Machine Learning BootcampIntroduction to DS & ML using PythonA robust introduction to Data Science and Machine Learning using Python. This course starts with a refresher of basic Python that will be useful for the course and then moves into linear algebra concepts using NumPy. After that they go into data visualization options and methods within Python and finally they touch on important machine learning algorithms.PythonOnline EducationModeratehttps://bit.ly/2VfuijJThis link should come attached with a coupon to pay 11 for the course.
5
Python Data Science HandbookIntroduction to DS & ML using PythonVery similar to the bootcamp material, although Jake comes at it from a bit of a different angle, with different problems. IMO It's very important to review these algorithms and methods in different contexts to see how generalizable and useful they can be.PythonBookModeratehttps://jakevdp.github.io/PythonDataScienceHandbook/The book is available for free on his Github, but as he suggests if you enjoy his work it would make sense to purchase it.
6
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic ThinkingConceptual understanding of fundamentalsThis book provides an overview of the terminology and concepts that underly data science. This book doesn't teach how to do data science, but is a place to start.EnglishBookBeginnerAvailable on Amazon
7
Pandas Cookbook: Recipes for Scientific Computing, Time Series Analysis and Data Visualization using PythonPandas (Python)Fairly comprehensive overview of Pandas. There are a ton of tips and tricks in here that you will likely spend way too much time searching for if you only use online resources.PythonBookBeginnerAvailable on Amazon
8
Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlowScikit-Learn & TensorFlow (Python)Provides a nice sruvey of machine learning and deep learning methods. Assumes familiarity with Python and machine learning fundamentals.PythonBookModerateAvailable on Amazon
9
Codecademy Introduction to PythonIntroduction to PythonA beginner class for learning Python in a hands on environment. One great thing about this class is it all happens in an online IDE which means there's no requirement to install anything on your computer. It allows for one to quickly get to actual programming instead of spending time at the beginning setting up your computer. This removes a lot of the roadblocks that can start a true beginner. Additionally, the class is entirely setup as a walkthrough with no video lectures. This makes it easy to pick up a topic/lesson and take a module quickly wherever you are, no sound required. From a beginners perspective, this is a great first step class.PythonOnline EducationBeginnerhttps://www.codecademy.com/learn/learn-pythonThe free class offers a lot, but it's still based in Python 2.
10
Deep Learning with PythonIntroduction to Deep Learning with Keras in PythonThis book provides a history of deep learning, an introduction to the concepts and topics relevant to understanding deep learning, and then walk throughs of different deep learning methods using Keras. The book was written by Francois Chollet, the lead developer at Google for Keras. It's clearly written and a great way to quickly dive into deep learning methods and approaches. Additionally, Chollet stays away from confusing looking mathematical equations and insteads writes out any relevant equations in Python code. This approach is surprisingly effective as it makes it clear what the equation is doing and how the deep learning method is using that math to develop models from the data.PythonBookModerateAvailable on AmazonThe quality of the physical book is poor, pages started ripping out of my book within two weeks of use. However, the book comes with a free PDF version as well after you purchase.
11
Hands-On Machine Learning with Scikit-Learn and TensorflowScikit-Learn & TensorFlow (Python)Provides a nice survey of machine learning and deep learning methods. Assumes familiarity with Python.PythonBookModeratehttps://bit.ly/2FT5FUAThe PDF of the books is free online, but you can also support the author and buy the book on Amazon.
12
The Hundred-Page Machine Learning BookMachine LearningProvides a knowledge compression of ML approaches all in 100 pages. It's a relateable and easy to understand jump into machine learning.English and MathBookBeginnerhttp://themlbook.com/wiki/doku.phpThe funding model is to read the book and then pay for it based on the value you think you got out of it. You can also buy the book on Amazon.
13
Beginner SQL Track on TreehouseIntroduction to SQLProvides an easy to use and quick introduction to SQL. SQL is often not required to conduct Machine Learning, but is often needed to querry the databases where your data will come from so you can perform Machine Learning. This class teaches you 90% of what you will need to extract the data important to you for your Machine Learning projects.SQLOnline EducationBeginnerhttps://teamtreehouse.com/tracks/beginning-sqlThis is not a comprehensive SQL course, it will quickly get you up to a functional level with SQL so you can pull the data you need and start manipulating it in Python.
14
Python TutorSupport ResourceThis is a very helpful website that visually shows you what is happening in your code as it is executing. It will help you understand how your code works and why you may be stuck on an error.PythonOnline EducationBeginnerhttp://pythontutor.com/
15
Coursera Deep Learning SpecializationDeep LearningAndrew Ng did a lot over the last decade to make machine learning and deep learning a household name. He is one of the founders of Coursera and his Machine Learning course on Coursera is still probably one of the most popular courses ever on the platform. This specialization does a great job of breaking down the math and walking you through the code step by step for neural networks, CNNs, and RNNs. It's a great overview of everything deep learning has to offer.PythonOnlineAdvancedhttps://www.coursera.org/specializations/deep-learning
16
Data FramedGeneral DiscussionThis podcast has a wide variety of experts from the field as guests and does a great job of discussing data science in applied practical terms. Each interview follows a similar pattern. The guest is asked what they are known for in the field, how they became a data scientist, what problems they currently are working on in the real world, and where they see the future of data science going.EnglishPodcastBeginnerhttps://www.datacamp.com/community/podcast
17
Pattern ClassificationMachine LearningThis is a timeless, excellent, comprehensive, and very clear book on machine learning with a practical, not math heavy approach. The authors explain the concepts and the reasoning behind the mathematical formulae in a super clear and simple fashion. It is a defining book in the field that anyone wanting to become an expert in the field should read and use as a reference.RBookModeratehttps://amzn.to/2uJncrW
18
Pattern Recognition - Lecture Notes, North Carolina UniversityMachine LearningA series of lecture notes from Professor Osuna on machine learning. The slides are extremely clear, simple and full of step by step examples.ROnline EducationModeratehttps://psi.engr.tamu.edu/courses/
19
Statistical Learning in R - Stanford UniversityMachine LearningAn introductory-level course in supervised learning in R. The lectures are not math heavy and focus on explaininhg the concepts behind the algorithmsROnline EducationModeratehttps://stanford.io/1Ry9D60
20
Numerical Linear AlgebraLinear AlgebraA course that teaches linear algebra using NumPy, PyTorch, and programming.PythonOnlineAdvancedhttps://github.com/fastai/numerical-linear-algebra
21
Intro to Deep Learning with PyTorchDeep LearningAn overview course of deep learning taught using PyTorch.PythonOnlineModeratehttps://www.udacity.com/course/deep-learning-pytorch--ud188
22
Practical Deep Learning for CodersDeep LearningA great course that walks you through how to build state of the art DL models in minutes. It's user friendly API integrates directly with PyTorch and makes building state of the art models extremely easy.PythonOnlineAdvancedhttps://course.fast.ai/
23
University of Washington Machine Learning SpecializationMachine LearningThis is a Machine Learning specialization through Coursera taught by professors from the University of Washington. IMO this course does a great job of going deeper into the math behind linear and logistic regression.PythonOnlineModeratehttps://www.coursera.org/specializations/machine-learning
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100