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Data Science and Engineering with Spark

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From edX: This course “will teach student how to perform data science and data engineering at scale using Spark, a cluster computing system well-suited for large-scale machine learning tasks. It will also present a integrated view of data processing by highlighting the various components of data analysis pipelines, including exploratory data analysis, feature extraction, supervised learning, and model evaluation. Students will gain hands-on experience building and debugging Spark applications. Internal … Continue Reading

Try Python

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From Code School: “Explore the basics of Python and learn what it means to store and manipulate numbers and words as well as make decisions with your program. Course Overview: Birds & Coconuts: Get started with Python by calculating how many swallows it takes to carry a coconut. Spam & Strings: Learn how to store characters in a string to combine, dissect, and slice words. Conditional Rules of Engagement: Explore … Continue Reading

Linear Algebra (MIT)

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“This course covers matrix theory and linear algebra, emphasizing topics useful in other disciplines such as physics, economics and social sciences, natural sciences, and engineering…. This course has been designed for independent study. It provides everything you will need to understand the concepts covered in the course.” The course covers the following topics: Systems of linear equations Row reduction and echelon forms Matrix operations, including inverses Block matrices Linear dependence and … Continue Reading

Statistical Learning (Stanford University)

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“This is an introductory-level course in supervised learning, with a focus on regression and classification methods. The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines. Some unsupervised learning methods are discussed: principal components and clustering (k-means and hierarchical). This … Continue Reading

Intro to Machine Learning

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From Udacity: “Machine Learning is a first-class ticket to the most exciting careers in data analysis today. As data sources proliferate along with the computing power to process them, going straight to the data is one of the most straightforward ways to quickly gain insights and make predictions. Machine learning brings together computer science and statistics to harness that predictive power. It’s a must-have skill for all aspiring data analysts … Continue Reading

Databases (Stanford University)

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This Database course from Stanford University consists of a set of “mini-courses” that are “based around video lectures and/or video demos. Many of them include in-video quizzes to check understanding, in-depth standalone quizzes, and/or a variety of automatically-checked interactive programming exercises. Each mini-course also includes a discussion forum and pointers to readings and resources.” The courses are organized into suggested pathways, as follows: Practical Relational Databases and SQL Practical Relational Databases and SQL … Continue Reading

Codecademy – Learn SQL

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From Codecademy: “In this course, you’ll learn how to communicate with relational databases through SQL. You’ll learn–and practice with 4 projects–how to manipulate data and build queries that communicate with more than one table. Why learn SQL? We live in a data-driven world: people search through data to find insights and inform strategy, marketing, operations, and a plethora of other categories. There are a ton of businesses that use large, … Continue Reading

Data Science 101

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From Cognitive Class: “Find out the truth about what Data Science is. Hear from real practitioners telling real stories about what it means to work in data science. You can start creating your own data science projects and collaborating with other data scientists using IBM Data Science Experience. Course Syllabus Module 1: Defining Data Science Module 2: What do data science people do? Module 3: Data Science in Business Module … Continue Reading

Data Science Essentials

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from edX: “Demand for data science talent is exploding. Develop your career as a data scientist, as you explore essential skills and principles with experts from Duke University and Microsoft. In this data science course, you will learn key concepts in data acquisition, preparation, exploration, and visualization taught alongside practical application oriented examples such as how to build a cloud data science solution using Microsoft Azure Machine Learning platform, or … Continue Reading

Learning Python for Data Analysis and Visualization

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From Udemy: “Learn python and how to use it to analyze, visualize and present data. Includes tons of sample code and hours of video. What Will I Learn? Have an intermediate skill level of Python Programming Use the Jupyter Notebook Environment Use the numpy library to create and manipulate arrays. Use the pandas module with Python to create and structure data. Learn how to work with various data formats within Python, … Continue Reading