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Master Computer Science on Coursera



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E.g., 2017-09-23
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Oct 17th 2017

Learn everything you need to know to get started building a MongoDB-based app. This course will go over basic installation, JSON, schema design, querying, insertion of data, indexing and working with the Python driver. We will also cover working in sharded and replicated environments. In the course, you will build a blogging platform, backed by MongoDB. A brief Python introduction is included in the course.

Average: 7.1 (20 votes)
Self Paced

Explore theory and practice, and work with tools like R, Python, and Azure Machine Learning to solve advanced data science problems. In this data science course, you will explore the theory and practice of select advanced methods commonly used in data science.

Average: 4.5 (2 votes)
Self Paced

The ability to analyze data with Python is critical in data science. Learn the basics, and move on to create stunning visualizations.

Average: 6.1 (15 votes)

Self Paced

Join us on the frontier of bioinformatics and learn how to look for hidden messages in DNA without ever needing to put on a lab coat. In the first half of this course, we'll investigate DNA replication, and ask the question, where in the genome does DNA replication begin? You will learn how to answer this question for many bacteria using straightforward algorithms to look for hidden messages in the genome.

Average: 10 (1 vote)
Self Paced

Get hands-on experience building and deriving insights from machine learning models using R, Python, and Azure Machine Learning. Machine learning uses computers to run predictive models that learn from existing data in order to forecast future behaviors, outcomes, and trends.

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Self Paced

Traverse the data analysis pipeline using advanced visualizations in Python, and make machine learning start working for you.

Average: 9.1 (7 votes)

Sep 25th 2017

In this course you will learn about audio signal processing methodologies that are specific for music and of use in real applications. We focus on the spectral processing techniques of relevance for the description and transformation of sounds, developing the basic theoretical and practical knowledge with which to analyze, synthesize, transform and describe audio signals in the context of music applications.

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Sep 25th 2017

Case Studies: Analyzing Sentiment & Loan Default Prediction
In our case study on analyzing sentiment, you will create models that predict a class (positive/negative sentiment) from input features (text of the reviews, user profile information,...). In our second case study for this course, loan default prediction, you will tackle financial data, and predict when a loan is likely to be risky or safe for the bank.

Average: 5.8 (5 votes)
Sep 25th 2017

This course will introduce the learner to the basics of the python programming environment, including how to download and install python, expected fundamental python programming techniques, and how to find help with python programming questions. The course will also introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the DataFrame as the central data structure for data analysis.

Average: 6.2 (6 votes)
Sep 25th 2017

Case Study - Predicting Housing Prices
In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression.In this course, you will explore regularized linear regression models for the task of prediction and feature selection. You will be able to handle very large sets of features and select between models of various complexity. You will also analyze the impact of aspects of your data -- such as outliers -- on your selected models and predictions. To fit these models, you will implement optimization algorithms that scale to large datasets.

Average: 7.4 (5 votes)
Sep 25th 2017

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies.

Average: 6.1 (13 votes)

Sep 25th 2017

This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text.

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