Subject Syllabus
CB-703 (A) - Cognitive Science & Analytics
CSBS · Semester 7
Course Modules
Learn topic-wise with Hyper AI and revise using mapped PYQs.
Introduction to Analytics: DefinitionDescription & Evolution of AnalyticsHistory of Analytics, and Applicability of Analytics with development of Technology and ComputerHow Analytics entered mainstream Concepts of Analytics: Various overlapping concepts and fields of Analytics such as Data MiningMachine LearningArtificial Intelligence and Simulation Emerging Areas in Analytics: Understanding of emerging research areas of Analytics: Mathematical programmingEvolutionary computationSimulationMachine learning/data miningLogic-based models, andCombinations of categories Value Chain of Analytics: Descriptive Analytics Covering Exploratory Data Analysis & Basic of StatisticsDiagnostics Analytics: BI/AnalysisTrendPatternSimultaneous RelationshipPredictive Analytics: Cause-Effect Relationship and Futuristic prediction in terms of probabilitiesContinuous & Categorical PredictionsSimulationOptimizationMulti-faceted Intelligent Technology driven Analytics combining Machine Intelligence with Human Brain Processing Abilities Introduction & Evolution of Cognitive Science: Introduction to the study of cognitive sciencesBrief history of cognitive science development and Methodological concerns in philosophy Understand Brain and Sensory Motor Information: Fundamentals of Neuro ScienceProcessing of sensory information in the brain, and Brain Imaging Elements Language & Linguistic Knowledge: Background and details of Syntax & SemanticsUnderstanding of Generative Linguistic Memory & Processing: Theory of Information ProcessingFundamentals of Short term Memory
Data as a whole: Understanding of Data as a whole for distinguishing and relating various types of data and Categorization of Data: StructuredUnstructured DataQuantitative & Qualitative Data.Views of Data: Understanding Data as an interdisciplinary framework for learning methodologies: covering statistics, neural networks, and fuzzy logic Measurement & Scaling Concepts: Measurement of variables and commonly used statistical tools: Number of procedures for measurement of the variablesCategorization proceduresScale construction procedures and Techniques of data processing for qualitative as well as quantitative dataVarious types of Scales: NominalOrdinalInterval & Ratio Scales
Overview: High level overview of Categorization of Techniques: Inter-dependence Relationship Techniques and Dependence Relationship Techniques Overview of Commonly Used Inter-dependence Techniques: Factor AnalysisPrincipal Component Analysis (PCA)Cluster Analysis Overview of Commonly Used Dependence Techniques: RegressionLogistic Regression Analytics Value Chain &Application of Analytics across Value Chain: a.Basic statistical concepts such as Descriptive & Diagnostics statistics, concept of random variables, discrete and continuous random variables, confidence interval, hypothesis testing, analysis of variance and correlation. b.Predictive analytics techniques such as multiple linear regression, logistic regression, decision tree learning Clustering and forecasting techniques. c.Prescriptive analytics Concepts: linear programming, integer programming, goal programming & stochastic models d.Cognitive analytics Concepts: Text AnalyticsLearning AnalyticsData MiningCognitive SystemsCognitive ComputingLearning Data ScienceMachine LearningBig data Analytics and Business analytics
Fundamentals of Artificial Intelligence: Various areas of AI: a.Knowledge: Text AnalyticsTopic ModellingNatural Language Processing (NLP)Natural Language Generation (NLG)Natural Language Understanding (NLU)Named-entity recognition (NER) b.Perception: Image AnalyticsVideo Analytics & Audio Analytics c.Memory: Cognitive Engagement: BOTsVirtual & Digital AssistantsAugmented RealityVirtual RealityMixed Reality d.Learning: Intelligent Automation Spectrum of AI a.Reactive Machine: Low memory, works on Known rules, such as Object Detection/Games/Recommendations specific to known Rules b.Limited Memory: Memory used to learn and improve continuously such as Most ML ModelsAutomated Vehicles c.Theory of Mind: Machine Understands and responds such as BoTs/Virtual/Digital Assistants d.Self-Aware: Human like intelligence such as Super Robots in Space etc.
World Standard Methodology: CRISP-DM MethodologySEMMA Methodology Real Life Work around Multi-Variate Analytics: A few Selected Commonly used Techniques: Predictive & Classification ModelsRegressionClustering Real Life Work around Artificial IntelligenceMachine Learning and Deep Learning: A few Selected Commonly used Techniques& Algorithms: ANN(Artificial Neural Network)CNN(Convolutional Neural Network)RNN (Recurrent Neural Network)RN Architecture: LSTM, Bidirectional LSTM, Gated Recurrent Unit(GRU)CTRNN(Continuous Time RNN) CNN Architectures: VGG16AlexnetInceptionNetRestNetGooglenet.Object Detection models: R-CNN, Fast R-CNN, Faster R-CNN, cascade R-CNN.Mask RCNN, Single Shot MultiBox Detector (SSD) ,You Only Look Once (YOLO)Single-Shot Refinement Neural Network for Object Detection (RefineDet)Retina-Net Autoencoders: Denoising AutoencoderGAN Transformers: Attention based Encoder and Decoder: Eg- BERT(Bidirectional Encoder Representations from Transformers)Generative Pretrained Transformers GPT-3GPT-2BERT, XLNet, and RoBERTa.LAB EXERCISES: Structured Data Analytics: Segmentation & ClusteringClassification & PredictionForecasting Association Mining & Sequence Mining Textual Data Analytics: Natural Language Processing (NLP)Natural Language Generation (NLG)Natural Language Understanding (NLU)Named-entity recognition (NER) driven Analytics: Key Word ExtractionText SummarizationInsight Generation Image Analytics: Malaria/Carcinoma/COVID detectionVisual inspection for QA/QC Video Analytics: Motion based Behavior RecognitionBehavioural Observations, and Parkinson's Disease Prediction Audio Analytics: Speech to TextText to SpeechTranscript Services Artificial IntelligenceMachine Learning driven Automation: Banking Process AutomationHospital Triage Process Automation AR/VR enabled Guided Operations Conversational Analytics: Artificial IntelligenceMachine LearningAugmented RealityVirtual RealityRoboticsDigital/Virtual Assistant