Course Outline
1. Introduction to Machine Learning
- Defining Machine Learning
- How it expands the scope of data analysis
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Common business applications:
- Sales forecasting
- Customer segmentation
- Churn prediction
2. Bridging Data Analysis and Machine Learning
- Recap: Managing data with Pandas
- Transitioning from descriptive to predictive analysis
- Formulating a Machine Learning problem
3. Machine Learning Workflow (Simplified)
- Preparing the dataset
- Dividing data into training and testing sets
- Training a model
- Generating predictions
4. Data Preparation for Machine Learning
- Addressing missing values
- Encoding categorical variables
- Feature selection (introductory)
- Scaling (conceptual overview)
5. Supervised Learning (Hands-on)
Regression
- Linear Regression
- Use case: forecasting numerical values (e.g. sales volume, demand)
Classification
- Logistic Regression
- Use case: predicting binary outcomes (e.g. customer churn, fraud detection)
6. Unsupervised Learning
Clustering
- K-means clustering
- Use case: customer segmentation
7. Model Evaluation (Simplified)
- Comparing training and testing performance
- Accuracy (for classification tasks)
- Understanding basic errors (for regression tasks)
8. Interpreting Results
- Decoding model outputs
- Identifying patterns and trends
- Converting results into strategic business insights
9. Practical End-to-End Example
- Loading a dataset
- Preparing and cleaning data
- Training a model
- Evaluating performance
- Extracting key insights
Requirements
Prerequisites
- Foundational knowledge of Python
- Familiarity with Pandas and dataset manipulation
- Understanding of basic data analysis concepts
Target Audience
- Data Analysts
- Business Analysts with some Python experience
- Professionals who have completed the Python for Data Analysis course or equivalent training
- Beginners in the field of Machine Learning
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
Course - Artificial Intelligence (AI) Overview
Working from first principles in a focused way, and moving to applying case studies within the same day
