Applied Data Science Specialization

开始时间: 05/21/2018 持续时间: Unknown

所在平台: Coursera专项课程

课程类别: 其他类别

大学或机构: CourseraNew



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This is an action-packed specialization is for data science enthusiasts who want to acquire practical skills for real world data problems. It appeals to anyone interested in pursuing a career in Data Science, and already has foundational skills (or has completed the Introduction to Applied Data Science specialization). You will learn Python - no prior programming knowledge necessary. You will then learn data visualization and data analysis. Through our guided lectures, labs, and projects you’ll get hands-on experience tackling interesting data problems. Make sure to take this specialization to solidify your Python and data science skills before diving deeper into big data, AI, and deep learning.


4 courses

Python for Data Science
Upcoming session: May 21
This introduction to Python will kickstart your learning of Python for data science, as well as programming in general. This beginner-friendly Python course will take you from zero to programming in Python in a matter of hours. Module 1 - Python Basics •

Data Visualization with Python
Upcoming session: May 21
"A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential rol

Data Analysis with Python
Upcoming session: May 21
Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaning

Applied Data Science Capstone
Starts July 2018
This capstone project course will give you a taste of what data scientists go through in real life when working with data. You will learn about why data cleaning and munging is an important part of data science and how it occupies more than 80% of a data scientist’s daily work. You will learn about location data and different location data providers, such as Foursquare. You will learn how to make RESTful API calls to the Foursquare API to retrieve data about venues in different neighborhoods around the world. You will also learn how to be creative in situations where data are not readily available by scraping web data and parsing HTML code. You will utilize python and pandas to manipulate data, which will help you help you refine your skills for analyzing data and creating interesting visuals. By the end of the first part of the course you would have compared different neighborhoods and shared your results. Data Scientists also need to be able to work with different kinds of machine learning techniques. In the second part of this course, you will build and apply a machine learning model using the geospatial data from the first part of the project as well as additional data sources, to investigate and attempt to predict neighborhood attributes using techniques like regression, decision trees, clustering, classification, etc. Storytelling and presentation is a very important part of a Data Scientist’s job. By the end of course you would have shared Jupyter notebooks of your implementation and written a detailed report describing your findings. You will also perform peer review of other’s projects.


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Applied Data Science Specialization-