Machine LearningPython ProgrammingPredictive AnalyticsData ProcessingData Visualization (DataViz)Python LibrariesData Pre-ProcessingWeb ScrapingBig Data ProductsRecommender Systems
Python Data Products for Predictive Analytics 專項課程
Build Predictive Systems with Accuracy. Collect, model, and deploy data-driven systems using Python and machine learning.
提供方
您將學到的內容有
Discover how to transform data and make it suitable for data-driven predictive tasks
Understand how to compute basic statistics using real-world datasets of consumer activities, like product reviews and more
Use Python to create interactive data visualizations to make meaningful predictions and build simple demo systems
Perform simple regressions and classifications on datasets using machine learning libraries
您將獲得的技能
關於此 專項課程
5,119 次近期查看
Python data products are powering the AI revolution. Top companies like Google, Facebook, and Netflix use predictive analytics to improve the products and services we use every day. Take your Python skills to the next level and learn to make accurate predictions with data-driven systems and deploy machine learning models with this four-course Specialization from UC San Diego.
This Specialization is for learners who are proficient with the basics of Python. You’ll start by creating your first data strategy. You’ll also develop statistical models, devise data-driven workflows, and learn to make meaningful predictions for a wide-range of business and research purposes. Finally, you’ll use design thinking methodology and data science techniques to extract insights from a wide range of data sources. This is your chance to master one of the technology industry’s most in-demand skills.
Python Data Products for Predictive Analytics is taught by Professor Ilkay Altintas, Ph.D. and Julian McAuley. Dr. Alintas is a prominent figure in the data science community and the designer of the highly-popular Big Data Specialization on Coursera. She has helped educate hundreds of thousands of learners on how to unlock value from massive datasets.
應用的學習項目
You’ll start by creating your first data strategy. You’ll also develop statistical models, devise data-driven workflows, and learn to make meaningful predictions for a wide-range of business and research purposes. Finally, you’ll use design thinking methodology and data science techniques to extract insights from a wide range of data sources. This is your chance to master one of the technology industry’s most in-demand skills.
可分享的證書
完成後獲得證書
100% 在線課程
立即開始，按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
中級
需要一些相關領域經驗。需要一些相關經驗。
完成時間大約為5 個月
建議 2 小時/週
英語（English）
字幕：英語（English）, 法語（French）, 巴西葡萄牙語, 俄語（Russian）, 西班牙語（Spanish）
可分享的證書
完成後獲得證書
100% 在線課程
立即開始，按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
中級
需要一些相關領域經驗。需要一些相關經驗。
完成時間大約為5 個月
建議 2 小時/週
英語（English）
字幕：英語（English）, 法語（French）, 巴西葡萄牙語, 俄語（Russian）, 西班牙語（Spanish）
此專項課程包含 4 門課程
Basic Data Processing and Visualization
134 個評分
This is the first course in the four-course specialization Python Data Products for Predictive Analytics, introducing the basics of reading and manipulating datasets in Python. In this course, you will learn what a data product is and go through several Python libraries to perform data retrieval, processing, and visualization.
Design Thinking and Predictive Analytics for Data Products
42 個評分
This is the second course in the four-course specialization Python Data Products for Predictive Analytics, building on the data processing covered in Course 1 and introducing the basics of designing predictive models in Python. In this course, you will understand the fundamental concepts of statistical learning and learn various methods of building predictive models. At each step in the specialization, you will gain hands-on experience in data manipulation and building your skills, eventually culminating in a capstone project encompassing all the concepts taught in the specialization.
Meaningful Predictive Modeling
33 個評分
This course will help us to evaluate and compare the models we have developed in previous courses. So far we have developed techniques for regression and classification, but how low should the error of a classifier be (for example) before we decide that the classifier is "good enough"? Or how do we decide which of two regression algorithms is better?
Deploying Machine Learning Models
41 個評分
In this course we will learn about Recommender Systems (which we will study for the Capstone project), and also look at deployment issues for data products. By the end of this course, you should be able to implement a working recommender system (e.g. to predict ratings, or generate lists of related products), and you should understand the tools and techniques required to deploy such a working system on real-world, large-scale datasets.
提供方
加州大学圣地亚哥分校
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
常見問題
完成专项课程后我会获得大学学分吗？
Can I just enroll in a single course?
我可以只注册一门课程吗？
Can I take the course for free?
我可以免费学习课程吗？
此课程是 100% 在线学习吗？是否需要现场参加课程？
完成专项课程需要多长时间？
Do I need to take the courses in a specific order?
Will I earn university credit for completing the Specialization?
完成专项课程后我会获得大学学分吗？
還有其他問題嗎？請訪問 學生幫助中心。
