Our live, tutor-led training course on Machine Learning is designed to provide you with a solid foundation in this exciting field.
Guided by an experienced instructor in real time, this course blends interactive lectures, discussions, and practical exercises to ensure you gain both theoretical understanding and hands-on experience.
Over the course of the training, you’ll explore essential concepts such as data preprocessing, machine learning algorithms, and model evaluation techniques. A highlight of the program is a hands-on activity where you’ll build a simple machine learning model with step-by-step guidance from your tutor.
This live format offers the unique advantage of direct interaction with the tutor, allowing you to ask questions, clarify doubts, and receive personalized feedback throughout the session. You’ll also participate in discussions on the ethics and future of machine learning, helping you approach this field with a well-rounded perspective.
Course Modules
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Fundamentals of Machine Learning:
Definition and key concepts
• Types of Machine Learning:
o Supervised Learning
o Unsupervised Learning
o Reinforcement Learning
• Real-world applications and examples -
Data Pre-processing:
• Importance of data quality
• Data cleaning and transformation
• Feature selection and engineering -
Machine Learning Algorithms:
Overview of popular algorithms:
o Linear Regression
o Decision Trees
o k-Nearest Neighbors (k-NN)
o Support Vector Machines (SVM)
• When to use each algorithm -
Model Evaluation and Validation:
Training vs. Testing datasets
• Cross-validation techniques
• Evaluation metrics:
o Accuracy
o Precision
o Recall
o F1-Score -
Hands-On Activity: Building a Simple Model:
Data loading
• Preprocessing
• Training
• Evaluation
• Building a linear regression model
• Result analysis and improvement -
Ethics and Future of Machine Learning:
Ethical considerations in ML (bias, privacy, etc.)
• Future trends and advancements
