LLMs for Predictive Analytics Training Course
Predictive analytics involves extracting insights from existing data sets to identify patterns and forecast future outcomes and trends.
This instructor-led, live training (available online or onsite) is designed for intermediate-level data scientists and business analysts who want to leverage large language models (LLMs) to predict trends and behaviours across various industries.
Upon completion of this training, participants will be able to:
- Grasp the core principles of LLMs and their significance in predictive analytics.
- Deploy LLMs to analyse and forecast data within diverse industry sectors.
- Assess the efficacy of predictive models utilising LLMs.
- Integrate LLMs into current data processing workflows.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical application.
- Hands-on implementation in a live laboratory environment.
Customisation Options
- To arrange bespoke training for this course, please contact us.
Course Outline
Introduction to Predictive Analytics
- Overview of predictive analytics
- Role of LLMs in predictive modelling
- Case studies: Successful predictive analytics projects
Fundamentals of Large Language Models
- Understanding LLM architecture
- Training and fine-tuning LLMs
- LLMs versus traditional statistical models
Data Preparation and Processing
- Data collection and cleaning
- Feature engineering for predictive modelling
- Utilising LLMs for data enrichment
Building Predictive Models with LLMs
- Selecting the appropriate LLM for your data
- Training LLMs for predictive tasks
- Evaluating model performance
Advanced Techniques in Predictive Analytics
- Time series forecasting using LLMs
- Sentiment analysis for market prediction
- Anomaly detection in large datasets
Integrating LLMs into Business Processes
- Deploying LLMs for real-time predictions
- Monitoring and maintaining predictive models
- Ethical considerations in predictive analytics
Hands-on Lab: Predictive Analytics Project
- Defining project objectives
- Implementing a predictive model with LLMs
- Analyzing results and iterating on the model
Summary and Next Steps
Requirements
- A grasp of fundamental machine learning concepts
- Practical experience with Python programming
- Familiarity with data analysis and visualisation tools
Target Audience
- Data scientists
- Business analysts
- IT professionals wishing to understand the application of LLMs in analytics
Need help picking the right course?
southafrica@nobleprog.co.za or +27 (0)10 005 5793