Data Science for Leader

Short Description:

Data Driven organizations has competitive advantage but building an effective Data Science Organization can seem complex and challenging.

Description:

Data Driven organizations have completive advantage but building an effective Data Science Organization can seem complex and challenging. Be the leader your data team needs! You’ve heard of data science and big data, but how do you leverage them to drive value? In this course, learn how to assemble, evaluate, and develop a data science enterprise and renew yourself as a data leader, even if you have never worked in data science before. Become conversant in the field and design strategies for supporting your team’s data science projects. Students aren’t expected to master the technical information themselves. This course is presented with a focus on managing your team and moving it forward which will then advance to making you understand how to build and manage an effective Data driven organization as a leader.

Course Code/Duration:

BDT247 / 1 – Day

Learning Objectives:

• Gain insights into the dynamics of data-driven organizations and their competitive advantages.
• Acquire skills to establish and manage an effective Data Science Organization, overcoming complexities.
• Develop proficiency in harnessing data science and big data for generating tangible value.
• Master the art of team management, empowering you to lead and champion data science projects within your organization.

• Basic level Knowledge of Data Science

• For anyone interested in becoming Data Leader among few titles like Data Managers, Data Analyst, Data Scientist, Data Engineer, Business Intelligence and Analytics Engineer, DevOps, Data Wrangler etc.

• For anyone interested in becoming Data Leader among few titles like Data Managers, Data Analyst, Data Scientist, Data Engineer, Business Intelligence and Analytics Engineer, DevOps, Data Wrangler etc.

Course Outline:

Getting Started

• Course Introduction
• Articulate the importance of data science in the organization’s overall digital strategy
• Advocate for data-driven practices in your organization

Making case for Data Science

• The Data Science process
• The importance of data
• Understand the importance of clean, complete, and quantity of data

Data Science Principles

• Analytics Taxonomy
• End to End data science
• Data Guided Decision Process
• Role of Data Science in Digital Process transformation

Data Science Areas and Roles

• The Difference Between Business Analytics (BI), Data Analytics and Data Science
• Data Science vs. Machine Learning
• Compare AI vs ML vs DL
• Discuss how to identify which kinds of technique to be applied for specific use case
• Understand the popular Machine offerings like Amazon Machine Learning, TensorFlow, Azure Machine Learning, Spark MiLB, Python and R etc.
• Understand the relation between Data Engineering and Data Science
• Identify when to use or not use Machine Learning

Leading an AI/Data Science Organization

• Use cases in various domains
• Recognizing opportunities for Data Science
• Building an effective Data and AI team
• Lead a data science and analytics workforce

Conclusion

• Industry Use Case Studies
• Best Practices
• Reference material
• Next steps

Training material provided: Yes (Digital format)