Course Outline
1. Introduction to Machine Learning
- Defining Machine Learning
- Extending the scope of data analysis
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Common business applications:
- Sales forecasting
- Customer segmentation
- Churn prediction
2. Transitioning from Data Analysis to Machine Learning
- Recap: Working with data in Pandas
- Shifting from descriptive to predictive analysis
- Defining a Machine Learning problem statement
3. Simplified Machine Learning Workflow
- Dataset preparation
- Splitting data (training vs. testing sets)
- Model training
- Generating predictions
4. Data Preparation for Machine Learning
- Managing missing values
- Encoding categorical variables
- Feature selection (overview)
- Scaling (conceptual introduction)
5. Supervised Learning (Practical Session)
Regression
- Linear Regression
- Application: Forecasting numerical values (e.g., sales, demand)
Classification
- Logistic Regression
- Application: Determining binary outcomes (e.g., churn, fraud detection)
6. Unsupervised Learning
Clustering
- K-means clustering
- Application: Customer segmentation
7. Simplified Model Evaluation
- Comparing training vs. testing performance
- Accuracy (for classification tasks)
- Understanding basic error metrics (for regression)
8. Interpreting Results
- Making sense of model outputs
- Spotting patterns and trends
- Converting results into business insights
9. End-to-End Practical Example
- Loading the dataset
- Data preparation and cleaning
- Training the model
- Evaluating performance
- Extracting key insights
Requirements
Prerequisites
- Fundamental knowledge of Python
- Familiarity with Pandas and handling datasets
- Understanding of core data analysis concepts
Target Audience
- Data Analysts
- Business Analysts with basic Python proficiency
- Professionals who have completed the Python for Data Analysis course or possess equivalent skills
- Beginners in the field of Machine Learning
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3200 € + VAT*
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Testimonials (2)
Getting people that never used AI some repetition in prompting and people that do use AI to consider different methods to using it.
Matthew Gay - Tarsus Pharmaceuticals
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