Course Outline
1. Introduction to Machine Learning
- What is Machine Learning
- How it extends data analysis
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Common business use cases:
- Sales forecasting
- Customer segmentation
- Churn prediction
2. From Data Analysis to Machine Learning
- Recap: working with data in Pandas
- Moving from descriptive to predictive analysis
- Defining a Machine Learning problem
3. Machine Learning Workflow (Simplified)
- Preparing the dataset
- Splitting data (train vs test)
- Training a model
- Making predictions
4. Data Preparation for Machine Learning
- Handling missing values
- Encoding categorical variables
- Feature selection (basic)
- Scaling (conceptual overview)
5. Supervised Learning (Hands-on)
Regression
- Linear Regression
- Use case: predicting numerical values (e.g. sales, demand)
Classification
- Logistic Regression
- Use case: binary outcomes (e.g. churn, fraud)
6. Unsupervised Learning
Clustering
- K-means clustering
- Use case: customer segmentation
7. Model Evaluation (Simplified)
- Train vs test performance
- Accuracy (classification)
- Basic error understanding (regression)
8. Interpreting Results
- Understanding model outputs
- Identifying patterns and trends
- Translating results into business insights
9. Practical End-to-End Example
- Load dataset
- Prepare and clean data
- Train a model
- Evaluate performance
- Extract insights
Requirements
Prerequisites
- Basic Python knowledge
- Familiarity with Pandas and working with datasets
- Understanding of basic data analysis concepts
Target Audience
- Data Analysts
- Business Analysts with basic Python knowledge
- Professionals who completed Python for Data Analysis or equivalent
- Beginners in 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*
Contact us for an exact quote and to hear our latest promotions
Testimonials (2)
the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose
Guillaume GAUTIER - OLEA MEDICAL
Course - MLflow
I enjoyed participating in the Kubeflow training, which was held remotely. This training allowed me to consolidate my knowledge for AWS services, K8s, all the devOps tools around Kubeflow which are the necessary bases to properly tackle the subject. I wanted to thank Malawski Marcin for his patience and professionalism for training and advice on best practices. Malawski approaches the subject from different angles, different deployment tools Ansible, EKS kubectl, Terraform. Now I am definitely convinced that I am going into the right field of application.
