About This Course
The Machine Learning with Python course provides a practical introduction to machine learning concepts, algorithms, and model development using Python. Participants will learn how to preprocess data, build predictive models, evaluate performance, and deploy machine learning solutions to solve real-world business and data challenges. Through hands-on exercises and real datasets, learners will gain experience with popular machine learning techniques, Python libraries, and modern AI frameworks used across industries.
Machine Learning with Python
Build practical machine learning solutions using Python and industry-standard libraries.
Data Preparation
Learn how to clean, transform, and prepare datasets for machine learning projects.
Predictive Modelling
Develop regression, classification, clustering, and deep learning models.
Model Deployment
Explore model evaluation, deployment strategies, and modern machine learning workflows.
Course Curriculum
• Introduction to Machine Learning
• Machine Learning Applications
• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning
• Machine Learning Workflow
• Model Evaluation Fundamentals
• Data Preprocessing Techniques
• Handling Missing Data
• Managing Outliers
• Feature Selection
• Dimensionality Reduction
• Data Normalization
• Data Scaling
• Linear Regression
• Multiple Regression
• Polynomial Regression
• Regularization Methods
• Regression Model Evaluation
• Logistic Regression
• Binary Classification
• Decision Trees
• Ensemble Methods
• Classification Model Evaluation
• Introduction to Unsupervised Learning
• K-Means Clustering
• Hierarchical Clustering
• Cluster Analysis
• Clustering Evaluation Metrics
• Neural Network Fundamentals
• Deep Learning Concepts
• TensorFlow Introduction
• Keras Framework
• Convolutional Neural Networks
• Recurrent Neural Networks
• Cross-Validation Techniques
• Feature Importance Analysis
• Model Explainability
• Handling Imbalanced Data
• Bias and Fairness in AI
• Model Deployment Strategies
• Production Machine Learning
• Cloud-Based Machine Learning Services
• Machine Learning Trends
• Emerging AI Technologies
Skills You'll Gain
Develop practical skills that can be applied immediately in real-world trading scenarios.
Registration & Pricing
Everything you need to know before enrolling.
Feedback
Marios Zindilis
SCP Academy was the key for me to open new doors in my career, leading me down paths I would never have thought of. Apart from Knowledge I have been taught to value persistence, to be curious and to focus on specific and timely goals, both in career as well as in life.
Marios Kairinos
I attended my first course in 2015 with the dream of becoming an IT professional. I have registered for the MCSA course and since then I have never stop learning. I have completed successfully the Azure and Office 365 courses which helped me find my dream job. Now I can ask for more and I know who can help me take them.
Evagoras Pourgourides
SCP Academy helped me learn more than I could ever imagine. The courses enriched me with knowledge and professional skills that i use in my job
Alexandros Louca
Following my passion for technology was one of the best decisions I ever made. In SCP Academy I have found and attended courses that advanced my career to the next level.
Giota Achilleos
SCP academy was the key for me to step to success. Regarding the knowledge that I gained from the university the academy offered to me more skills to succeed my goals and my dreams. SCP academy has offered to me professional courses that helped me to start my new career in Malta.
Panos Iacovides
It is never too late to make an advancement in your career and SCP Academy has helped me to achieve that. Started with the CCNA R&S Certificate and now moving on to the MCSA Certificate with more to follow. SCP Academy has also taught me that learning is a never ending process and I should make the most of it on a daily basis, making every second count. Did you know there are 86400 seconds in a day? Interesting huh?
Course Features
- Lectures 0
- Quizzes 0
- Duration 60 hours
- Skill level All levels
- Language English
- Students 10
- Assessments Yes
