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Business Analytics with Python is a Program

Business Analytics with Python

Self-paced

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Full program description

Business Analytics with Python

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

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

Pre-requisites

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

Price

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