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1.INTRODUCTION TO DATA SCIENCE, BIG DATA, DEEP LEARNING AND MACHINE LEARNING- 6 hours
- Definition of different concepts related to data science (Data Science)
- Theory of different methods such as Machine Learning (supervised, unsupervised and semi)
- Illustration with real cases (Morale Machine)
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2.DATA-DRIVEN MANAGEMENT - 6 hours
- Data-Driven business models
- Legal challenges of Big Data - Big (Brother) Data
- Data-Driven Organitzation: new corporate strategy
- Artificial Intelligence Canvas model
- Testimony of a Data Scientist on the impact of Big Data on their company
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3.EXPLORATORY DATA ANALYSIS - 12 hours
- Practice on real Big Data cases
- Use of open data
- Illustration with issues in HR, Marketing, Health, etc
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4.SUPERVISED AND UNSUPERVISED MACHINE LEARNING MODELS - 24 hours
- Python practice of supervised Machine Learning algorithm (Knn, RF, SVM)
- Python practice of unsupervised Machine Learning algorithm (PCA, AGNES, DIANA)
- Application to real business cases
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5.DATA STORY TELLING AND DATA VISUALIZATION - 14 hours
- Data Storytelling: methodology
- Design principles: color, shape and visual thinking
- Learning data interaction techniques
- Explore the most common tools for creating graphics: Tableau or Power BI
- Data visualization tools: Reporting and Dashboarding
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6.PROJECT AND REAL BUSINESS CASE - 10 hours
- Application to a real case: your business
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