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Duration 21 hours
Course Outline
Introduction
- Defining the scope of Predictive AI
- The evolution of predictive analytics
- Foundations of machine learning and data mining
Data Acquisition and Preparation
- Sourcing relevant data
- Refining and formatting data for analysis
- Recognizing data types and origins
Exploratory Data Analysis (EDA)
- Using visualization to gain insights
- Applying descriptive statistics and summarization
- Detecting patterns and correlations within data
Statistical Modeling
- Foundations of statistical inference
- Regression analysis techniques
- Building classification models
Machine Learning Algorithms for Forecasting
- Introduction to supervised learning algorithms
- Decision trees and random forests
- Essentials of neural networks and deep learning
Model Assessment and Selection
- Interpreting accuracy and performance metrics
- Implementing cross-validation methods
- Managing overfitting and optimizing models
Real-World Applications of Predictive AI
- Industry-specific case studies
- Ethical aspects of predictive modeling
- Limitations and challenges in Predictive AI
Practical Project
- Creating a predictive model using a dataset
- Deploying the model for predictions
- Reviewing and interpreting outcomes
Requirements
- A foundational understanding of basic statistics
- Proficiency in at least one programming language
- Comfort with data management and spreadsheet tools
- Previous experience in AI or data science is not 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