Certified Artificial Intelligence For Data Analysts Training in Brisbane

Certified Artificial Intelligence (AI) for Data Analysts Training Course Outline

Module 1: AI Foundations for Data Analysts

• AI, Machine Learning, and Generative AI Explained
• LLMs, Copilots, and Core AI Terminology
• The Modern AI-Driven Analytics Lifecycle
• AI Strengths, Limitations, and Hallucinations
• Human Validation of AI Outputs
• Lab: Explore an AI Copilot for Data Analysis

Module 2: AI-Assisted Data Preparation

• AI-Powered Data Collection Techniques
• Cleaning and Preparing Data Using AI
• Data Transformation and Feature Engineering
• AI-Assisted SQL Query Generation
• Data Quality Validation Using AI
• Lab: Clean and Prepare a Dataset Using AI

Module 3: EDA and Machine Learning Fundamentals

• AI-Assisted Exploratory Data Analysis
• Detecting Trends, Patterns, and Anomalies
• Machine Learning Fundamentals for Analysts
• Supervised vs. Unsupervised Learning Approaches
• Selecting the Right ML Approach with AI
• Lab: Perform AI-Assisted EDA

Module 4: Generative AI for Analytics Productivity

• Prompt Engineering for Data Analysts
• Generating SQL, Python Code, and Formulas
• AI for Documentation and Code Explanation
• AI-Assisted Root Cause Analysis
• Validating and Improving AI-Generated Outputs
• Lab: Generate and Validate Analytics Code

Module 5: Predictive Analytics and Decision Support

• Predictive Analytics Fundamentals
• Forecasting and Trend Analysis Using AI
• Prescriptive Analytics and AI-Driven Decisions
• Real-World Analytics Case Studies
• Workshop: Build an AI-Assisted Forecasting Solution

Module 6: AI-Powered Visualisation and Storytelling

• AI-Assisted Dashboard Design and Chart Selection
• AI-Generated Business Narratives and Executive Reporting
• Human Validation of AI-Generated Reports
• Lab: Generate an Executive Dashboard Summary

Module 7: Enterprise AI, Governance, and Ethics

• Enterprise AI Platforms, Frameworks, and APIs
• AI Copilots in Analytics Workflows
• Data Privacy, Security, and Compliance
• Ethical AI, Bias, and Explainability
• Future Trends in AI-Augmented Analytics
• Activity: Review and Improve an AI Analysis

Module 8: Capstone: End-to-End AI Analytics Workflow

• Framing the Business Problem and Data Strategy
• Collect and Prepare Data Using AI
• AI-Assisted EDA and Anomaly Detection
• Generate SQL and Python Code with AI
• Build Visualisations and Dashboards
• Create Executive Insights and Recommendations
• Validate AI Outputs and Present Findings
• Capstone Workshop: End-to-End AI Analytics Project

Who Should Attend Certified Artificial Intelligence (AI) for Data Analysts Training

This course is designed for data analysis professionals seeking to leverage AI in their data analysis practices. The ideal audience includes:

• Data Analysts
• Business Analysts
• Data Scientists
• Data Engineers
• BI Analysts
• Research Analysts
• Data Visualisation Specialists

Prerequisites of Certified Artificial Intelligence (AI) for Data Analysts Training

There are no formal prerequisites for attending this AI for Data Analysts Training. However, having a basic understanding of data analysis principles, familiarity with data analysis tools and techniques, and an interest in artificial intelligence and machine learning applications would be beneficial for the delegates.

Certified Artificial Intelligence (AI) for Data Analysts Training Course Overview

The Certified Artificial Intelligence (AI) for Data Analysts training course is designed to equip data analysis professionals with the knowledge and skills to integrate AI into their data analysis practices. As AI continues to revolutionise data analysis, this course offers a comprehensive understanding of how AI can enhance data collection, preprocessing, analysis, visualisation, and reporting. By mastering these AI-driven techniques, participants can significantly advance their careers, opening up new opportunities in the rapidly evolving field of AI-enhanced data analysis.

This 1-day AI for Data Analysts Training course provide delegates with comprehensive knowledge of AI in data analysis, AI-driven data collection and preprocessing, machine learning fundamentals, advanced AI techniques, predictive and prescriptive analytics, AI tools and frameworks, data visualisation and reporting, and ethical and legal considerations. Delegates will gain practical knowledge on implementing AI tools and platforms, integrating AI with existing data analysis workflows, and following best practices for AI in data analysis. Real-world examples and case studies will demonstrate the transformative potential of AI in enhancing data analysis practices and improving overall data-driven decision-making.

Course Objectives

• Understand the role and benefits of AI in modern data analysis practices
• Learn to use AI for automated data collection and preprocessing
• Develop skills to implement machine learning models and advanced AI techniques
• Explore AI tools for predictive and prescriptive analytics
• Gain insights into AI-driven data visualisation and interactive reporting
• Discuss the ethical and legal implications of using AI in data analysis

After attending this training, delegates will be able to confidently integrate AI techniques into their data analysis practices. They will have the ability to automate complex pre-processing tasks, apply machine learning models to uncover hidden patterns, and utilise predictive and prescriptive analytics for better decision-making. Delegates will also be capable of leveraging AI tools and frameworks to enhance their reporting and visualisation outputs, ensuring greater clarity and accuracy in communicating insights.

What's included in this Certified Artificial Intelligence for Data Analysts Training

• World-Class Training Sessions from Experienced Instructors
• The Certified Artificial Intelligence for Data Analysts Training
• Digital Delegate Pack