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Duration 21 hours
Course Outline
Introduction
- Defining the scope of Predictive AI
- Examining the historical context and progression of predictive analytics
- Reviewing fundamental principles of machine learning and data mining
Data Acquisition and Preprocessing
- Collecting relevant and high-quality data
- Cleaning and structuring data for analytical use
- Identifying different data types and their origins
Exploratory Data Analysis (EDA)
- Using data visualization to gain insights
- Applying descriptive statistics for data summarization
- Detecting underlying patterns and correlations
Statistical Modeling
- Foundations of statistical inference
- Conducting regression analysis
- Implementing classification models
Machine Learning Algorithms for Forecasting
- Surveying supervised learning approaches
- Utilizing decision trees and random forests
- Introducing neural networks and deep learning concepts
Model Assessment and Selection
- Interpreting model accuracy and key performance indicators
- Employing cross-validation methods
- Addressing overfitting and optimizing model parameters
Real-World Applications of Predictive AI
- Reviewing industry-specific case studies
- Considering ethical implications in predictive modeling
- Recognizing the constraints and challenges of Predictive AI
Practical Project
- Constructing a predictive model using a provided dataset
- Deploying the model to generate forecasts
- Analyzing and interpreting the final outcomes
Requirements
- Foundational knowledge of statistics
- Basic proficiency in at least one programming language
- Experience managing data and working with spreadsheets
- No previous background in AI or data science is necessary
Target Audience
- IT professionals
- 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
