Course Overview
The course will provide students with a basic understanding of Business Analytics using Python. Students wanting to enrol in this course should have attended the course Introduction to Coding
Who Should Attend
IT personnel
Course Duration
8 hours
Course Outline
- What is Business Analytics
- Identify main outcomes from business analytics
- Identify skill sets a business analytics expert has
- Define Business Analytics
- Contrast data analytics with business analytics and business intelligence
- Differentiate between Descriptive, Diagnostic, Predictive and Prescriptive analytics
- Describe CRISP-DM as an Analytics Methodology
- Analytics Methodology
- Describe and illustrate the application of CRISP-DM into current business practice
- Describe current Business Intelligence and Business Analytics practices in Industry
- Explain and illustrate Data Preparation and Data Understanding
- The contrast between structured and unstructured data
- List and Describe common Analytics Models
- Explain and Demonstrate Evaluation of Models
- Supervised Learning Tutorial
- Identify data characteristics using pandas
- Execute data preparation using pandas and sci-kit learn
- View data features as a result of data preparation
- Conduct supervised learning on a dataset
- Describe and execute cross-validation
- Read and evaluate models and algorithms
- Describe common models used in supervised learning
- Other Business Analytics tools and Strategies
- Describe Supervised Learning
- Describe and demonstrate Clustering (Unsupervised Learning)
- Describe and demonstrate Text Analytics
- Describe and Demonstrate Process Optimization
- Describe and Demonstrate Graph Analysis
- Describe and contrast Business Intelligence and Visual Analytics
- Discuss differences to process and evaluation for each strategy
- Describe how each strategy applies to current business processes of HR, marketing, operations.
- List and describe other Advanced Analytics practices
- Common Analytics Traps
- Describe and demonstrate common analytics traps
Categories
More Information
- (Local Institution) NTUC LearningHub
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