Machine Learning Foundation Course
2 - Months Machine Learning Course
| Online Class | Physically Class |
|---|---|
| Course Title: Machine Learning Foundation Course Duration: 8 Weeks Lectures: 16 Weekly: 2 Days Time Duration: 2 Hours Quizzes: 2 Certificate: Included Training in: English / Urdu | Course Title: Machine Learning Foundation Course Duration: 8 Weeks Lectures: 16 Weekly: 2 Days Time Duration: 2 Hours Quizzes: 2 Certificate: Included Training in: English / Urdu |
Course Outline
- What is Machine Learning?
- Evolution of Machine Learning
- Machine Learning vs Traditional Programming
- Applications of ML in real life
- Why Machine Learning is important in today’s world
- Types of ML (Supervised, Unsupervised, Reinforcement Learning)
- How ML works? (Problem -> Data -> Model Training -> Testing -> Evaluation)
- Challenges in implementing Machine Learning models (Overfitting, Underfitting)
- Introduction to Math required for ML (Linear Algebra, Probability, Calculus, etc.)
- Importance of Mathematics in Machine Learning
- Linear Algebra basics (Matrices, Vectors)
- What is Data
- What is data pre-processing?
- Techniques for handling missing values (Removing Missing Data)
- Data Splitting (Training vs Testing)
- Introduction to supervised learning
- Concept of labeled data
- What are classification models?
- Types of learners (Lazy Learners vs Eager Learners)
- Support Vector Machine (SVM)
- Naïve Bayes
- K-Nearest Neighbor
- Introduction to regression
- Regression models
- Types of regression models
- Decision Trees for Regression
- Introduction to unsupervised Learning
- Difference between Supervised & Unsupervised Learning
- Introduction to deep learning
- Importance and applications of Deep Learning (Image recognition, NLP, etc.)
- How deep learning works?
- Predicting House Prices (Regression Problem)
- Predict whether an email is spam or not? (Classification Problem)
- Basics Of Machine Learning
Implementation of simple ML models - Gain basic knowledge of deep learning
- Junior Machine Learning Engineer
- AI/ML Intern
- Data Science Assistant
FAQ's
Machine learning helps businesses with important functions like fraud detection, identifying security threats, personalization and recommendations, automated customer service through chatbots, transcription and translation, data analysis, and more
After which, the model needs to be evaluated so that hyperparameter tuning can happen and predictions can be made. It’s also important to note that there are different types of machine learning which include supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning.
There are four types of machine learning algorithms: supervised, semi-supervised, unsupervised, and reinforcement.
Python. Python is likely the most popular language for ML, AI, and data analytics. It’s a high-level, general-purpose language, which makes it slower to execute than languages like C++
- Supervised learning, using labeled data.
- Unsupervised learning, using unlabeled data.
Reinforcement learning, using trial and error..
Python is one of the most important languages for starting out in machine learning and AI, but if you want to specialize, you’ll often need to supplement your Python skills with those of one of the other key programming languages.
SEO Person Salaries in Pakistan
| Skill Level | Avg Monthly Salary |
|---|---|
| Beginner Level |
35K to 45K
|
| Mid Level |
45K to 80K
|
| Experienced |
80K to 200K
|
| Freelancer |
Above 100K
|
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)
- Preparation for advanced ML and AI certifications
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