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AI+ Business Intelligence Practitioner™

Course code: NPAT820

Formerly known as AI+ Business Intelligence™

Empower Your Career with AI+ Business Intelligence Practitioner™ for Advanced Data Solutions

  • AI-Powered Business Intelligence: Use advanced AI tools to convert raw data into meaningful, actionable insights
  • Smarter Decision-Making: Enable faster, data-informed decisions that are closely aligned with core business goals
  • Strategic Growth: Uncover trends, emerging opportunities, and potential risks to support sustainable business growth
  • Data-Driven Innovation: Strengthen your strategy through predictive analytics and evidence-based decision-making.
75 EUR

91 EUR including VAT

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Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 40 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 40 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date		 Place
Type Course
duration		 Language Price without VAT
G Upon request Self-paced 40 hours en 285 EUR Register
G Upon request Self-paced 40 hours en 75 EUR Register
G Guaranteed course

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Course description

AI and BI Integration

Understand the fundamental concepts of Artificial Intelligence (AI) and Business Intelligence (BI) and how they work together to drive data-driven decision-making.

Python for BI

Master Python programming and its application in business intelligence, including advanced libraries and data visualisation techniques for effective analysis.

Data Preparation and Feature Engineering

Learn how to collect, evaluate, and prepare data for machine learning and AI models, ensuring high-quality datasets for analysis.

Machine Learning Models

Gain expertise in applying machine learning techniques to enhance business intelligence and leverage data for predictive insights.

Course structure

Module 1: Introduction to AI and BI Fundamentals

  • 1.1 Overview of AI and BI Integration
  • 1.2 Core Concepts in Business Intelligence
  • 1.3 Data Analysis Process and AI’s Role
  • 1.4 BI Trends and Challenges
  • 1.5 Case Study
  • 1.6. Hands on Activity

Module 2: Python for AI-Driven Business Intelligence

  • 2.1 Python Programming Fundamentals
  • 2.2 Advanced Python Libraries for BI
  • 2.3 Visualization with Python
  • 2.4 Hands on Activity

Module 3: Data Preparation and Feature Engineering with AI

  • 3.1 Data Collection Techniques
  • 3.2 Data Quality & Evaluation
  • 3.3 Advanced Data Preparation
  • 3.4 Hands on Activity

Module 4: Machine Learning (ML) for Business Intelligence

  • 4.1 ML Models for BI
  • 4.2 Hands on Activity

Module 5: Advanced AI and Generative AI for BI

  • 5.1 Deep Learning and Neural Networks for BI
  • 5.2 Generative AI for BI
  • 5.3 Hands on Activity

Module 6: Statistical Analysis with AI Tools

  • 6.1 Statistical Analysis for BI
  • 6.2 Time Series Analysis
  • 6.3 Hands on Activity

Module 7: AI-Powered Business Intelligence Tools

  • 7.1 AI in BI Platforms
  • 7.2 Power BI Essentials
  • 7.3 Tableau Essentials
  • 7.4 Hands on Activity

Module 8: Prompt Engineering for AI-Driven BI

  • 8.1 Introduction to Prompt Engineering
  • 8.2 Crafting Effective Prompts
  • 8.3 Hands on Activity

Module 9: Communication Skills

  • 9.1 Data Storytelling & Communication
  • 9.2 Solution Presentation

Module 10: Capstone Project

  • 10.1 Capstone Project 1
  • 10.2 Capstone Project 2
  • 10.3 Capstone Project 3

Prerequisites

  • Basic Computer skills: General understanding of everyday software applications
  • Fundamental Data Concepts: A basic awareness of data analysis principles is beneficial but not required
  • Open to All: Including all experience levels, with a genuine interest in AI, machine learning, and business intelligence

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