Machine Learning Foundation Course in Rawalpindi and Islamabad
- Course Duration : 8 weeks/ 2 Months
- Study Lecture : 24 Lectures
- Class Duration: 2 Hours
- Skill Level : Basic of ML
- Certificate : Included
- Training in : English / Urdu
More Courses For You !
Category :
Data & Tech
20 Reviews :
Price :
Coming Soon
Machine Learning Foundation Course Overview:
This Machine Learning Foundation Course is ideal for beginners who want to step into the exciting field of AI and machine learning. With easy-to-follow explanations, simplified math, and engaging projects, you will learn the core principles that drive intelligent systems. The course also emphasizes hands-on experience through practical exercises, case studies, and projects, ensuring a robust understanding of the subject matter.
Course Objectives
- Understand the core concepts of machine learning and its real-world applications
- Explore key algorithms like KNN, SVM, Naive Bayes, and Linear Regression
- Apply basic clustering and dimensionality reduction techniques like PCA
- Evaluate models using metrics such as accuracy, precision, and recall
- Work on hands-on projects like spam detection and loan approvalLearn to prepare and preprocess data for ML models
What You Will Learn
- Introduction to ML: Supervised vs Unsupervised Learning
- Algorithms like KNN, SVM, Naive Bayes, Linear Regression
- Basic clustering and dimensionality reduction (PCA)
- Data preprocessing, feature engineering, and model tuning
- Evaluation metrics like accuracy, precision, recall
- Mini projects: Spam detection, Loan approval predictor, House price estimator
What You’ll Get
- Machine Learning Foundation Certificate
- Hands-on project experience with real datasets
- Confidence to explore advanced AI, Deep Learning, or Data Science
- Access to learning resources and cheat sheets
Career & Internship Opportunities
- AI Intern / ML Trainee
- Junior Data Annotator
- Junior Machine Learning Support
- Freelance ML tasks (data cleaning, labelling, basic modelling
Why Choose Us
- A simple, practical approach to learning ML
- Industry-focused projects and real datasets
- Learn from practicing AI professionals
- Supportive learning community and mentor feedback
- Pathway to deep learning, NLP, and advanced AI courses