Text size
Line height
Text spacing
Course content
Sections:
38
•
Activities:
48
•
Resources:
58
General
Welcome Announcement
Course Orientation
Welcome (Start Here)
1.1. Module Introduction
1.2. What is Data?
Reading Assignment
Quiz (Ungraded): Data Introduction
1.3. Data Collection and Preprocessing
1.4. Visualizing Data
Lesson: Visual Aspects of Data
1.5. Exploring Data
1.6. Feature Engineering
1.7. Module Wrap-up
2.1. Module Introduction
2.2. Machine Learning - An Introduction
2.3. Introduction to Unsupervised Machine Learning
2.4. Clustering
2.5. Module Wrap-up
3.1. Module Introduction
3.2. Introduction to Supervised Machine Learning
3.3. Regression
3.4. Classification
3.5. Loss Functions
3.6 Popular Supervised Machine Learning Algorithms
3.7. Module Wrap-up
4.1. Module Introdution
4.2. The Artificial Intelligence (AI) Landscape
4.3. Basics of Artificial Neural Networks
4.4. Perceptron
4.5. Multi-Layer Perceptron
4.6. Activation Functions
4.7. Loss Functions for Neural Networks
4.8. Gradient Descent
4.9. Optimizers
4.10. Back Propagation
4.11. Overfitting and Underfitting
4.12. Cross Validation
4.13. Dropout Regularization
4.14. Model vs. Hyper Parameters Tuning
4.15. Case Study
4.16. Module Wrap-up
Course Conclusion
Course Completion Certificate
Instructors
- RI2 courses43 students
Rabia Irfan
- 2 courses43 students
Momina Moetesum
Dr. Momina Moetesum is an Assistant Professor in Faculty of Computing at the School of Electrical Engineering and Computer Sciences (SEECS), National University of Sciences and Technology (NUST), Pakistan. She completed her Ph.D. in Computer Science in 2021 from Bahria University, Islamabad, Pakistan. During her Ph.D. she secured the Hubert Curien PERIDOT Research Grant and worked in LIPADE, Université Paris Cité, France, on her research titled “Deformation Estimation and Classification of Graphomotor Impressions-An Application to Neuropsychological Assessments”. Her research interests include Online and Offline Handwriting Analysis for Brain Disorder Identification, DocumentAI, Computer Vision, and Natural Language Processing. She was the recipient of Best Poster Award at the Doctoral Consortium organized by ICDAR in 2017 in Kyoto, Japan. She co-organized the programming events at 3rd IAPR TC10/TC11 Summer School on Document Analysis (SSDA2019) held in Islamabad, Pakistan in 2019. She has been serving as program committee member in ICDAR since 2017 and was the publication chair in ICFHR 2023. She is also a member of IAPR standing committee on Equality, Diversity, and Inclusion. She has published 30+ articles in reputed conferences and Impact Factor journals. Dr. Momina is an expert in Artificial Intelligence, Machine Learning, Deep Learning, and Computer Vision. She has been associated with academia for the past 10 years. She has conducted several trainings in machine learning and computer vision to help individuals gain the required skills.
- JY1 courses43 students
Junaid Younas
Enrolment options
This introductory course is designed for enthusiasts from diverse non-computing backgrounds who want to harness the power of machine learning. Whether you're in healthcare, marketing, finance, education, or any other field, this course will equip you with the knowledge and skills to apply machine learning for data and predictive analysis effectively. Participants in this course will be familiarized with basic data pre-processing and exploratory analysis techniques followed by a solid understanding of unsupervised and supervised machine learning algorithms, enabling them to implement classification, regression, and clustering models for various applications. They will also gain practical knowledge of advanced machine learning algorithms like artificial neural networks, allowing them to build, train, and optimize neural network models for complex problems. Each module includes a combination of introductory lectures, hands-on exercises, case studies, and projects to reinforce the concepts and skills learned. The micro-credential with conclude with a Capstone project that will enable you to apply the various concepts learned throughout the course.
- Teacher: Rabia Irfan
- Teacher: Momina Moetesum
- Teacher: Junaid Younas
- Enrolled students: 43
Price: PKR 7,000
This course includes
Resources