Lecture 1 - Intro to Data Analytics. What is Learning Analytics?
Lecture 2 - Academic Analytics, and Educational Data Mining
Lecture 3 - Four Levels of Analytics
Lecture 4 - Four Levels of Learning Analytics Overview - II
Lecture 5 - Data Collection from Different learning environment
Lecture 6 - Data collection in TELE
Lecture 7 - Data Preprocessing
Lecture 8 - Ethics in Learning Analytics, Student Privacy
Lecture 9 - Demo of Weka
Lecture 10 - Introduction to Machine Learning - Part 1
Lecture 11 - Introduction to Machine Learning - Part 2
Lecture 12 - Training and testing data
Lecture 13 - Performance Metrics - I
Lecture 14 - Performance Metrics - II
Lecture 15 - Performance Metrics - III
Lecture 16 - Demo of Orange
Lecture 17 - Descriptive Analytics - I
Lecture 18 - Descriptive Analytics - II
Lecture 19 - Charts - I
Lecture 20 - Charts - II
Lecture 21 - Charts - III
Lecture 22 - Comparing Charts
Lecture 23 - Descriptive Analytics – Example I
Lecture 24 - Descriptive Analytics – Example II
Lecture 25 - Excel tool
Lecture 26 - Diagnostics Analytics
Lecture 27 - Correlation
Lecture 28 - Correlation Matrix
Lecture 29 - Spearman’s Rank Correlation
Lecture 30 - Data Mining
Lecture 31 - iSAT
Lecture 32 - Diagnostic Analytics - SPM
Lecture 33 - Sequential pattern mining (SPM-II)
Lecture 34 - Differential Sequence Mining (DSM)
Lecture 35 - Process Mining
Lecture 36 - Diagnostic Analytics - Clustering
Lecture 37 - K-means Clustering
Lecture 38 - Hierarchical Clustering
Lecture 39 - Clustering - Examples
Lecture 40 - Predictive Analytics
Lecture 41 - Linear Regression
Lecture 42 - Multiple Regression
Lecture 43 - Logistic Regression
Lecture 44 - Linear Regression - Example
Lecture 45 - Predictive Analytics - II
Lecture 46 - Naive Bayes Classifier
Lecture 47 - Decision Tree
Lecture 48 - Decision Tree Classifier
Lecture 49 - DT, NB - Examples
Lecture 50 - Text Analytics
Lecture 51 - Introduction to NLP
Lecture 52 - NLP-II
Lecture 53 - NLP-Tools
Lecture 54 - NLP-Examples
Lecture 55 - Intro Multimodal Learning Analytics
Lecture 56 - Affective Computing - 1
Lecture 57 - Affective Computing - 2
Lecture 58 - Eye Tracking
Lecture 59 - Revision of Learning Analytics tools course
Lecture 60 - Source of Data collection and Research Community
Lecture 61 - Machine Learning tools used in industry
