Data Science for Business 2020
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Содержание
About the Course
Data Science for Business. MAGoLEGO course.
Spring 2020. Module 4
Department of Data Analysis and Artificial Intelligence, School of Computer Science.
Instructors
Course outline
- Introduction to data science
- Data mining, statistics, machine learning, optimization
- Case studies
- Increasing business impact
Content
| № | Date | Title | Abstract |
|---|---|---|---|
| 1 | 10.04.2020 | Introduction to data science. | Introduction to data science and its role in industry. Examples of real world use cases. |
| 2 | 17.04.2020 | Working with data. | Data cleaning and preparation. ETL process. Basic data analysis and visualization. |
| 3 | 24.04.2020 | Data mining, machine learning, statistics | Types of ML algorithms, applicability, training and testing, solution quality. |
| 4 | 15.05.2020 | Case study 1: Customer segmentation | The goal of the case is to group customers into clusters based on some customer similarity metrics.
Algorithms: Unsupervised learning. Clustering: k-means, agglomerative; Dimensionality reduction: PCA. |
| 5 | 22.05.2020 | Case study 2: Churn modeling | The goal of the case is to predict which customers are going to leave the service within a given time.
Algorithms: Supervised learning. Classification: Logistic regression, Decision trees, Random forest. |
| 6 | 29.05.2020 | Case study 3: Pricing | The goal of the case is to determine the optimal pricing for goods and services.
Algorithms: Supervised learning. Regression: linear and non-linear models. |
| 7 | 05.06.2020 | Case study 4: Industrial analytics | The goal of the case is to predict an output of the production line and find optimal parameter setting.
Algorithms: Supervised learning. Regression: non-linear optimization. |
| 8 | 12.06.2020 | Case study 5. Sales territory design | The goal of the case is to select locations of the sales offices to maximize the coverage under constrained resources.
Algorithms: clustering and geo-analytics approaches. |
| 9 | 19.06.2020 | Impacting the business | How to create a visible impact on business with analytics |
Textbooks
- Provost, Foster, Fawcett, Tom. Data Science for Business: What you need to know about data mining and data-analytic thinking. O'Reilly Media, Inc.", 2013.
- James, G. et al. An introduction to statistical learning. Springer, 2013.
- Siegel, E. Predictive analytics: The power to predict who will click, buy, lie, or die. John Wiley & Sons, 2016.
