4.3
星
185 個評分

Marco Brambilla 另外 +1 位授課教師

9,357 人已註冊

提供方

EIT 数字

米兰理工大学

Data Science for Business Innovation

EIT 数字

課程信息

47,416 次近期查看

The Data Science for Business Innovation nano-course is a compendium of the must-have expertise in data science for executives and middle-management to foster data-driven innovation. The course explains what Data Science is and why it is so hyped. 
You will learn:
* the value that Data Science can create
* the main classes of problems that Data Science can solve
* the difference is between descriptive, predictive, and prescriptive analytics
* the roles of machine learning and artificial intelligence. 

From a more technical perspective, the course covers supervised, unsupervised and semi-supervised methods, and explains what can be obtained with classification, clustering, and regression techniques. It discusses the role of NoSQL data models and technologies, and the role and impact of scalable cloud-based computation platforms. All topics are covered with example-based lectures, discussing use cases, success stories, and realistic examples.

Following this nano-course, if you wish to further deepen your data science knowledge, you can attend the Data Science for Business Innovation live course https://professionalschool.eitdigital.eu/data-science-for-business-innovation

可靈活調整截止日期

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可分享的證書

完成後獲得證書

100% 在線

立即開始，按照自己的計劃學習。

初級

完成時間大約為7 小時

英語（English）

字幕：法語（French）, （歐洲人講的）葡萄牙語, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）

您將學到的內容有

What is data science

How data science, machine learning, and data-driven innovation can benefit business outcomes

Foundational concepts and intuitions about machine learning techniques

您將獲得的技能

Data Science
Business Analytics
Decision-Making
Data Analysis
Big Data

可靈活調整截止日期

根據您的日程表重置截止日期。

可分享的證書

完成後獲得證書

100% 在線

立即開始，按照自己的計劃學習。

初級

完成時間大約為7 小時

英語（English）

字幕：法語（French）, （歐洲人講的）葡萄牙語, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）

授課教師

授課教師評分

4.39/5 （53 個評分）

Marco Brambilla

Professor

Politecnico di Milano

9,357 個學生

1 門課程

Emanuele Della Valle

Associate Professor

Politecnico di Milano

9,357 個學生

1 門課程

提供方

EIT 数字

EIT Digital is a European education and innovation organisation with a mission to foster digital technology innovation and entrepreneurial talent for economic growth and quality of life. By linking education, research, and business, EIT Digital empowers digital top talent for the future.

EIT Digital provides online and face-to-face Innovation and Entrepreneurship education to raise quality, increase diversity and availability of the top-level content provided by 20 leading technical universities around Europe. The universities deliver a unique blend of the best of technical excellence and entrepreneurial skills and mindset to digital engineers and entrepreneurs at all stages of their careers. The academic partners support Coursera’s bold vision to enable anyone, anywhere, to transform their lives by accessing the world’s best learning experience. This means that EIT Digital gradually shares parts of its entrepreneurial and academic education programmes to demonstrate its excellence and make it accessible to a much wider audience. EIT Digital’s online education portfolio can be used as part of blended education settings, in both Master's and Doctorate programmes, and for professionals as a way to update their knowledge.

米兰理工大学

Politecnico di Milano is a scientific-technological University, which trains engineers, architects and industrial designers.

授課大綱 - 您將從這門課程中學到什麼

週

週 1

完成時間為 1 小時

Introduction to Data-driven Business

This module introduces the course and offers some basic overview of the topics. It presents the crucial concepts related to data science and big data and provides an outlook on how to use them in real world settings for increasing business value.

完成時間為 1 小時

3 個視頻（總計 13 分鐘）, 2 個閱讀材料, 2 個測驗

3 個視頻

Welcome and Introduction4分鐘

Data-driven Decision Making for Data-centric Organizations2分鐘

What's Big Data? How Does It Relate to Data Science?6分鐘

2 個閱讀材料

Data-driven Decision Making for Data-centric Organizations15分鐘

What's Big Data? How Does It Relate to Data Science?15分鐘

2 個練習

Data-driven Decision Making for Data-centric Organizations3分鐘

Big Data and Data Science10分鐘

週

週 2

完成時間為 2 小時

Terminology and Foundational Concepts

In this module, you will learn the foundational concepts of machine learning and data science. You will understand how these techniques can be useful in terms of increased business value for organizations, thanks to the discussion of a very well known success story, namely Netflix, which can be deemed as a completely data-driven business. You will also understand how machine learning is different from programming.

完成時間為 2 小時

3 個視頻（總計 16 分鐘）, 3 個閱讀材料, 3 個測驗

3 個視頻

Success Story: Data Science at Netflix3分鐘

Machine Learning9分鐘

Solving Problems: Programming vs. Machine Learning3分鐘

3 個閱讀材料

Success Story: Data Science at Netflix30分鐘

Machine Learning slides20分鐘

Solving Problems: Programming vs. Machine Learning10分鐘

3 個練習

Success Story: Data Science at Netflix5分鐘

Machine Learning20分鐘

Solving Problems: Programming vs. Machine Learning30分鐘

週

週 3

完成時間為 3 小時

Data Science Methods for Business

In this module, you will learn the concepts and intuitions about the basic approaches for data analysis, including linear regression, naive Bayes, decision trees, clustering, and logistic regression. All the methods are presented starting from typical business uses and are covered in an intuitive way through a guided explanation of how the approach works on simple examples.

完成時間為 3 小時

5 個視頻（總計 25 分鐘）, 5 個閱讀材料, 5 個測驗

5 個視頻

Linear Regression for Price Prediction4分鐘

Classification of User-generated Content to Recommend Restaurants2分鐘

Product Recommendation Using Decision Trees and Random Forests2分鐘

Hiring Employees Using Logistic Regression8分鐘

K-means Clustering6分鐘

5 個閱讀材料

Linear Regression for Product Price Prediction10分鐘

Classification User-generated Content to Recommend Restaurants10分鐘

Product Recommendation Using Decision Trees and Random Forests10分鐘

Hiring Employees Using Logistic Regression10分鐘

Using k-means for Clustering10分鐘

5 個練習

Linear Regression30分鐘

Naive Bayes30分鐘

Decision Trees and Random Forests30分鐘

Logistic Regression30分鐘

K-means Clustering6分鐘

週

週 4

完成時間為 1 小時

Challenges and Conclusions

This module summarizes the concepts learned so far and introduces a set of challenges and risks that data-savvy managers must take into account when deciding for a data-driven strategy.

完成時間為 1 小時

2 個視頻（總計 12 分鐘）, 1 個閱讀材料, 1 個測驗

審閱

4.3

52 條評論

5 stars
59.04%
4 stars
23.40%
3 stars
10.63%
2 stars
3.72%
1 star
3.19%

來自DATA SCIENCE FOR BUSINESS INNOVATION的熱門評論

由 GS 提供2020年1月19日

A very well done course that showcases the main technologies applied in different scenarios. It was a good introduction to the world of applied data science.

由 SP 提供2020年5月23日

The knowledge was practical based and interesting; however better application of knowledge in real life would've been a great add-on.

由 UN 提供2022年1月18日

Data Science is the future and this course has given a fundamental principles of this technology.

由 CM 提供2021年5月15日

Great course, great content, the quiz questions are tricky which makes it really interesting

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Data Science for Business Innovation

Data Science for Business Innovation