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Business Analytics with Python is a Program

Business Analytics with Python


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Full program description

Business Analytics with Python

Course Overview

The course will provide students 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 skillsets 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
    • 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 scikitlearn
    • View data features as result of data preparation
    • Conduct supervised learning on 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

Course Objectives

Students will be:

·         Able to Describe different aspects of Business Analytics

·         Able to Describe CRISP-DM as a Framework for Analytics

·         Able to Identify Common Tools used in Business Analytics

·         Able to Describe Common Characteristics of Data

·         Able to Read, Compute and Visualize data from spreadsheet using Pandas Library

·         Able to Identify common Traps in Analytics


Learners are assumed to be able to:

  Have a moderate understanding in daily computer usage

  Have analytical skills to assess central concepts

  Possess a strong level of English to understand technical language

  Open mind

Medium of Instruction & Trainer

Medium of Instruction: English

Trainer: Trainee ratio is 1:25


$252.34 (before GST) / $270 (with GST)