Comprehensive Course in Data Science and Machine Learning with Python

 Course Objectives

In the rapidly evolving field of data science, proficiency in Python and machine learning is essential for leveraging data to drive business insights and decisions. This comprehensive course is designed to equip participants with practical skills and hands-on experience in data science and machine learning using Python. Participants will learn to apply data analysis techniques, build predictive models, and implement machine learning algorithms to solve real-world problems.

By the end of this course, participants will:

• Understand fundamental concepts of data science and machine learning.
• Gain proficiency in Python programming for data analysis and machine learning.
• Develop and deploy machine learning models using various algorithms.
• Master techniques for data preprocessing, visualization, and analysis.
• Implement best practices for model evaluation and performance optimization.

Course Outline

Module 1: Introduction to Data Science and Python

• Overview of data science and its applications
• Introduction to Python for data science: Basics and best practices
• Setting up the development environment: Tools and libraries

Module 2: Data Preprocessing and Exploration

• Data cleaning and preprocessing: Handling missing values and outliers
• Exploratory data analysis (EDA): Techniques for summarizing data
• Data visualization: Using libraries like Matplotlib and Seaborn to create meaningful charts

Module 3: Machine Learning Fundamentals

• Introduction to machine learning concepts: Supervised vs. unsupervised learning
• Building regression models: Linear and polynomial regression
• Classification algorithms: Logistic regression, decision trees, and k-Nearest Neighbors (k-NN)

Module 4: Advanced Machine Learning Techniques

• Ensemble methods: Random forests and gradient boosting
• Support Vector Machines (SVM) and neural networks
• Model evaluation: Metrics and techniques for assessing model performance

Module 5: Real-World Applications and Deployment

• Implementing machine learning models in real-world scenarios
• Model deployment: Strategies for integrating models into production systems
• Case studies: Applying data science to industry-specific problems

Target Group

This course is ideal for professionals, data analysts, and aspiring data scientists who want to deepen their knowledge and skills in data science and machine learning using Python. It is particularly beneficial for individuals seeking to transition into data science roles, enhance their technical capabilities, or apply machine learning techniques to their current positions. Additionally, those interested in solving complex data-driven problems and leveraging Python for data science will find this bootcamp valuable.

Course Cost

• 5-Day Training: €3,700
• 10-Day Training: €6,500

The course fee covers all training materials, access to online resources, and a certificate of completion. Discounts for group enrollments are available upon request.

This course is available on different dates upon request, providing flexibility to suit participants' schedules.

Organizers

This course is organized by the Geneva Institute of Business Management in partnership with its renowned collaborators across Europe. The Institute is known for delivering high-impact training programs that equip individuals with the skills needed to excel in data science and machine learning.