Data Science for Managers

This course equips professionals with the knowledge and tools to navigate the fast-evolving fields of digital transformation and machine learning. As businesses increasingly depend on data and technology for innovation and efficiency, understanding their intersection is critical. Participants will explore Industry 4.0 concepts, digital transformation, and data analytics to enhance operations and customer experiences. Practical frameworks like CRISP-DM for data-driven projects and DELTA-TA for technology integration are introduced, allowing learners to apply these methodologies in real-world contexts. In machine learning, participants will learn foundational concepts of supervised and unsupervised learning, along with the four levels of analytics: descriptive, diagnostic, predictive, and prescriptive. The course also covers neural networks and deep learning applications, focusing on current and future machine learning uses across industries, while addressing ethical considerations.

Digital transformation 
•    Industry 4.0 and digital transformation
•    Technology innovation and dependency on data
•    What is Big Data
•    What is Machine Learning
•    Big Data and Machine Learning

Predictive Analytics with Big Data
•    Foundations of Analytics
•    Analytics Frameworks
•    Why Big Data is better
•    Role in operational efficiency
•    Role in risk management

Machine Learning fundamentals
•    ML introduction and milestones
•    Types of machine learning
•    Fundamentals of ML workflow
•    Introducing Deep Learning 

Advanced Machine Learning concepts
•    Recent breakthroughs in ML
•    ChatGPT and AI tools
•    Role of cloud in ML
•    Machine Learning best practices

Contact:;+65 85124032    neurotek2025@gmail.com

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