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Applying Business Analytics | Syllabus


Lecture # Subject Title
Lecture Faculty: Taps Maiti
Week 1: Statistics – Data Driven Science
1 Statistics – Data Driven Science – Introduction
2 Data and Variables
3 Data Visualization
4 Statistical Thinking
Lecture Faculty: Taps Maiti
Week 2: Describing the Data
5 Describing the Data – Introduction
6 Mean – Measure of Central Tendency
7 Measures of Variability
8 Application and Mean of Variance
9 Application Using R
10 Percentile and Z–score
Lecture Faculty: Taps Maiti
Week 3: Data Distribution
11 Probability Distributions
12 Normal Distribution
13 Use of Normal Distribution
14 Binomial Distributions
Lecture Faculty: Taps Maiti
Week 4: Statistical Inference
15 Defining the Target
16 Point and Interval Estimators
17 Confidence Intervals
18 Inference on Two Populations
Lecture Faculty: Taps Maiti
Week 5: Simple Linear Regression
19 Probabilistic Relation
20 Linear Regression – Introduction
21 Case Study One: Building Maintenance
22 Case Study One: Building Maintenance (Continued)
23 Use of R
24 Case Study Two: Predicting Facebook Likes From Twitter Data
Lecture Faculty: Cheri SpeierPero, PhD
Week 6: Data Mining and Inferential Statistics
25 Data Mining – Introduction
26 Business Understanding
27 Framing a Research Question
28 Data Understanding and Preparation
29 Checking and Transforming Data
30 Inferential Data Mining Techniques – Part One
31 Inferential Data Mining Techniques – Part Two
Lecture Faculty: Cheri SpeierPero, PhD
Week 7: Decision Trees, Machine Learning and Optimization
32 Machine Learning
33 Introduction to NonInferential Techniques
34 Clustering Techniques
35 Decision Trees
36 Neural Networks
37 Optimization
38 Detecting Anomalies
39 Machine Learning Closure and Challenges
Lecture Faculty: Cheri SpeierPero, PhD
Week 8: Analyzing Text, Networks, Location and Imagery Data
40 Text Analytics – Part One
41 Text Analytics – Part Two
42 Network Analysis
43 Spatial – Temporal Analysis
44 Mobile – Location Based Analysis – Part One
45 Mobile – Location Based Analysis – Part Two
49 Imagery Analytics
50 Redux – Data Visualization