I gave these lectures as a part of the course "AI Skills Bootcamp" at the Department of Computer Science at University of Huddersfield (2022 Autumn Term).
Motivation and Use Cases
Introduction to Artificial Intelligence (AI) Introduction to Machine Learning (ML) Algorithms, Applications, and Handson: Linear and Logistic Regression Decision Tree and Random Forest Naive Bayes and Support Vector Machine (SVM) Dimensionality Reduction, KNN, and Gradient Boosting Neural Network (NN) and Recurrent Neural Network (RNN) KMeans and tSNE Data Preparation Techniques Feature Extraction Techniques Autoencoders and Linear Discriminant Analysis (LDA) Validation and Testing Building Email Spam Filter using Machine Learning Lectures on Inventory Control with Machine LearningI gave these lectures as a part of the course "AI Skills Bootcamp" at the Department of Computer Science at University of Huddersfield (2022 Autumn Term).
Introduction and Motivation
Inventory Tracking Inventory Control Stock Prediction Introduction to Time Series Data Statistical Methods for Time Series Forecasting (Part 1) Statistical Methods for Time Series Forecasting (Part 2) Machine Learning for Time Series Forecasting Part 1 Machine Learning for Time Series Forecasting Part 2 Python Packages for Time Series Analysis and Forecast Inventory Management Software Architecture Inventory Planning & Optimization Predicting BackOrders New Paradigms in Inventory Management Lectures on Data AnalysisI gave these lectures as a part of the module "Data Analysis Introduction" at the Department of Computer Science at University of Huddersfield (2022 Autumn Term).
Introduction to Data Analysis
Real World Examples of Data Analysis & Applications Basic Statistical Concepts Measures of Central Tendencies (Part 1) Measures of Central Tendencies (Part 2) Data Visualization and Data Design (Part 1) Data Visualization and Data Design (Part 2) Data Source: Finding Data in Real World Introduction to Dashboards Alternative data analytics tool  Python Lectures on Inferential StatisticsI gave these lectures as a part of the course "Probability and Statistics" at the Department of Computer Science and Engineering at Sejong University (2022 Spring Semester).
Probability and Random Variables
Probability Distributions (Continuous and Discrete) Expectation and Variance Introduction to Estimation Confidence Interval Test of Hypothesis Based on a Single Sample Test of Hypothesis Based on Two Samples SingleFactor Analysis of Variance (ANOVA) MultiFactor Analysis of Variance (ANOVA) Goodness of Fit Tests Python Codes for Inferential Statistics [Will be uploaded here] Lectures on Statistical LearningI gave these lectures as a part of the course "Introduction to Statistical Learning" at the Department of Computer Science and Engineering at Sejong University (2021/092021/12).
Introduction to Statistical Learning
Linear Regression Linear Regression Review Classification (Logistic Regression) Classification (Generative Models) Resampling (Crossvalidation, The Bootstrap) Model Selection and Regularization (Subset Selection, Lasso and Ridge Regression) Model Selection and Regularization (Dimension Reduction Methods) TreeBased Methods: Decision Tree Basics TreeBased Methods: Ensemble Learning Support Vector Machine (SVM) Unsupervised Learning (Principle Component Analysis, Clustering Methods) Python Codes for Statistical Learning [Python Basics] [Linear Regression] [Regression Review] [Classification] [Model Selection and Regularization] [Ensemble Learning] [SVM and Clustering] Lectures on MultimediaI gave these lectures as a part of the course "Multimedia" at the Department of Computer Science and Engineering at Sejong University (2021/092021/12).
Data Visualization: Introduction
Data Visualization: Design Multimedia Communications and Networks Content Distribution, Social Media, and Cloud Computing AR, VR, and Principles of Animation Introduction to Generative Adversarial Network (GAN) Please scroll down for lectures on other multimedia topics Lectures on Image ProcessingI gave these lectures as a part of the course "Image Processing" at the Department of Computer Science and Engineering at Sejong University (2020/1).
Introduction to Image Processing
Digital Image Fundamentals Intensity Transformations and Spatial Filtering (Part 1) Intensity Transformations and Spatial Filtering (Part 2) Filtering in the Frequency Domain (Part 1) Filtering in the Frequency Domain (Part 2) Image Restoration and Reconstruction Image Compression Image Segmentation Feature Extraction Lectures on MultimediaI gave these lectures as a part of the course "Multimedia" at the Department of Computer Science and Engineering at Sejong University (2019/2).
Multimedia Frameworks and Tools
Video Compression Principles Advanced Video Compression Techniques (AVC H.264 and HEVC H.265) Please scroll down for lectures on other multimedia topics Lectures on Probability and Statistics Programming with PythonI gave these lectures as a part of the course "Probability and Statistics Programming" at the Department of Computer Science and Engineering at Sejong University (2019/1).
Statistics with Python Practice 1
Statistics with Python Practice 2 Statistics with Python Practice 3 Statistics with Python Practice 4 Statistics with Python Practice 5 Please scroll down for lectures on other Probability and Statistics Programming topics Lectures on Image ProcessingI gave these lectures as a part of the course "Image Processing" at the Department of Computer Science and Engineering at Sejong University (2019/1).
Lectures Contents: TBA
Lectures on MultimediaI gave these lectures as a part of the course "Multimedia" at the Department of Computer Science and Engineering at Sejong University (2018/2).
Lectures Contents: TBA
Lectures on Probability and Statistics Programming in RI gave these lectures as a part of the course "Probability and Statistics Programming" at the Department of Computer Science and Engineering at Sejong University (2018/1).
Lectures on Internet of Things (IoT)I gave these lectures as a part of the course "Internet of Things: Protocols and Applications" at the Department of Computer Science and Engineering at Sejong University (2018/1).
Lectures Contents: TBA
Lectures on MultimediaI gave these lectures as a part of the course "Multimedia" at the Department of Computer Science and Engineering at Sejong University (2017/2).
Lectures on Object Oriented Programming (OOP) in C++I gave these lectures as a part of the course "Problem Solving and Lab: C++" at the Department of Computer Science and Engineering at Sejong University (2017/1).
Lectures on Random ProcessI gave these lectures as a part of the course "Random Process" at the Department of Information and Communication Engineering at Inha University, South Korea
Lectures on Wireless CommunicationsI gave these lecture as a part of the course "Advanced Data Communications and Wireless Networks" at the Department of CSE at Ahsanullah University of Science and Technology (AUST), Bangladesh (2013 and 2014).
Courses I Taught @University of DhakaAPECE302: Radio & Television Engineering (Grade: Junior, Session: 201213)
[Course Home] APECE402: Microwave & Satellite Communication (Grade: Senior, Session: 201112) [Course Home] [Lectures/Notices] APECE302: Radio & Television Engineering (Grade: Junior, Session: 201112) [Course Home] [Lectures/Notices] EEE1222: Basic Electronics (Grade: Freshman (2), Session: 201112) [Course Home] [Lectures/Notices] APECE308: Microprocessor & Assembly Language Programming (2006, 2007) APECE203: Electrical Machines & Measurements (2006) APECE406: Material Science (2006, 2007) APECE205: Physical Electronics & Electronic Devices (2007) Others Courses I Teach/Taught
