AI for Data Analytics and Predictive Insights

Duration: 2 Days • Classroom: Physical • HRDC: Claimable

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What you'll learn
  • Participants will gain an understanding of the basics of Flutter, including how to create layouts, handle user input, manage state, and connect to APIs.
  • Ability to create custom mobile apps.
  • Participants will have Hands-on experience to apply their newly acquired knowledge and skills in a real-world context.
Course description

This intensive hands-on workshop empowers participants to leverage AI for data analytics and predictive insights, enabling actionable intelligence from business data. Participants will learn to clean, process, analyze, and visualize data, build predictive models, and create dashboards for decision-making. Emphasis is on practical exercises and real-world projects, allowing participants to develop AI-powered solutions for forecasting trends, detecting patterns, and generating actionable insights applicable to finance, operations, marketing, and customer service. By the end of the workshop, attendees will gain the confidence and hands-on experience to apply AI for predictive decision-making, improve business performance, and anticipate future risks and opportunities.

Course content
  • AI in business analytics: benefits and challenges
  • Predictive vs descriptive vs prescriptive analytics
  • Case studies across finance, marketing, and operations
  • Overview of AI analytics tools: ChatGPT, Microsoft Co-Pilot, Google Gemini AI, Tableau, Power BI, n8n
  • Account setup, platform navigation, and environment configuration
  • Understanding data types: structured vs unstructured
  • Cleaning, normalizing, and transforming datasets
  • Handling missing and inconsistent data
  • Prepare a sample business dataset for AI analysis
  • Explore basic data cleaning techniques
  • Exploratory data analysis using AI
  • Detecting patterns, anomalies, and correlations
  • Feature selection for predictive modeling
  • Creating interactive dashboards
  • Visualizing trends, KPIs, and forecasts
  • Automating reports for decision-makers
  • Automating data ingestion, processing, and reporting
  • Integrating AI with corporate tools (Excel, Google Workspace, Slack, Teams)
  • Build an AI-powered analytics dashboard
  • Automate data collection and reporting workflow
  • Regression, classification, and time-series forecasting
  • Model selection and evaluation metrics
  • Understanding AI model outputs
  • Applying predictive models to real-world business cases
  • What-if analysis using AI
  • Risk assessment and opportunity identification
  • Build a predictive model for sales, customer churn, or financial forecasting
  • Evaluate model accuracy and refine predictions
  • Generate actionable recommendations based on insights
  • Improving model performance
  • Integrating predictive outputs into dashboards and workflows
  • Identify a real workplace dataset or challenge
  • Apply AI tools to clean, analyze, visualize, and generate predictive insights
  • Build a deployable dashboard or report for decision-making
  • Scaling AI analytics solutions across departments
  • Monitoring performance and ROI of AI models
  • Responsible AI practices and ethical considerations
  • Complete and present capstone project
  • Peer review and facilitator feedback
  • Develop a deployment roadmap for real-world application
  • Review and discussion of tools and concepts covered.
  • Q&A session to address any questions.
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This course includes:

English

2 Days

Physical Class

Certificate of Completion

HRDC Claimable

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