Full course description
Objective
Play different roles within a data science team, solve real challenges within the enterprise and leverage AI-powered technologies
Badge
Earn IBM's Enterprise Data Science in Practice badge
Audience
This course is only available to people affiliated with Illinois Tech
Credit
None, this is a not-for-credit course
Prerequisites
Complete the Getting Started with Enterprise Data Science course
Scope
- Data science team roles
- Data science method
- Data analysis tools
- Real-world use cases
Learning outcomes
- Understand the composition and working of a Data science team, including the different roles, processes, and tools
- Key statistics concepts and methods essential to finding structure in data and making predictions
- Internalize the data science methodology by learning to: (a) Characterize a business problem; (b) Formulate a hypothesis; (c) Demonstrate the use of methodologies in the analytics cycle; (d) Plan for execution
- Construct usable data sets by identifying and collecting the data required, and manipulating, transforming, and cleaning the data; demonstrating the ability to deal with data anomalies such as missing values, outliers, unbalanced data, and data normalization
- Hands-on experience with IBM Watson Studio, Data Refinery Spark, Jupyter Notebooks, and Python libraries
- Visualize statistical analysis, identify patterns, and effectively communicate findings to executive sponsors for business-driven decision-making