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Duration 21 hours
Course Outline
Introduction
- Defining the scope of Predictive AI
- The history and progression of predictive analytics
- Foundational principles of machine learning and data mining
Data Acquisition and Preparation
- Sourcing pertinent data
- Cleaning and structuring data for analysis
- Recognizing data types and origins
Exploratory Data Analysis (EDA)
- Visualizing data to derive insights
- Applying descriptive statistics and summarizing data
- Spotting patterns and correlations within datasets
Statistical Modeling
- Introductory concepts of statistical inference
- Conducting regression analysis
- Implementing classification models
Machine Learning Algorithms for Forecasting
- Surveying supervised learning algorithms
- Utilizing decision trees and random forests
- Basics of neural networks and deep learning
Model Assessment and Selection
- Interpreting model accuracy and performance indicators
- Employing cross-validation methods
- Addressing overfitting and optimizing model parameters
Real-World Uses of Predictive AI
- Industry-specific case studies
- Ethical dimensions of predictive modeling
- Constraints and challenges in Predictive AI
Practical Project
- Developing a predictive model using a specific dataset
- Deploying the model to generate forecasts
- Analyzing and interpreting final outcomes
Requirements
- Foundational knowledge of statistics
- Proficiency in at least one programming language
- Comfort with data management and spreadsheet tools
- No prior background in AI or data science is necessary
Target Audience
- IT practitioners
- Data analysts
- Technical personnel
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
