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Duration 21 hours
Course Outline
Introduction
- Defining the scope of Predictive AI
- The history and evolution of predictive analytics
- Foundational principles of machine learning and data mining
Data Collection and Preprocessing
- Sourcing relevant datasets
- Cleaning and formatting data for analysis
- Recognising different data types and their origins
Exploratory Data Analysis (EDA)
- Using visualisation techniques to extract insights
- Applying descriptive statistics and summarising data
- Detecting patterns and correlations within the data
Statistical Modeling
- Introduction to statistical inference
- Techniques in regression analysis
- Building classification models
Machine Learning Algorithms for Prediction
- Survey of supervised learning algorithms
- Utilising decision trees and random forests
- Basics of neural networks and deep learning
Model Evaluation and Selection
- Interpreting accuracy and performance indicators
- Applying cross-validation methods
- Managing overfitting and optimising models
Practical Applications of Predictive AI
- Industry-specific case studies
- Ethical implications of predictive modelling
- Recognising the limitations and challenges of Predictive AI
Hands-On Project
- Constructing a predictive model from a dataset
- Deploying the model to generate forecasts
- Analysing and interpreting the outcomes
Requirements
- Fundamental knowledge of statistics
- Basic experience with any programming language
- Comfort with data management and spreadsheets
- No previous experience in AI or data science is necessary
Target Audience
- IT professionals
- Data analysts
- Technical staff
Testimonials (3)
basics and loved the prepared documents and exercises
Rekha Nallam - GE Medical Systems Polska Sp. z o.o.
Course - Introduction to Predictive AI
Opportunity to use a pre-created models, understand how do they work and tweak them live and see the results. Choice ov VSCode with Jupyter was a perfect option for such way of leading the training.
Krzysztof - GE Medical Systems Polska Sp. z o.o.
Course - Introduction to Predictive AI
Difficult topics presented in simple, user-friendly way
