Introduction to ML: Introduction, Data Preparation Data Encoding Techniques Data Pre-processing techniques for ML applications. Feature Engineering: Dimensionality Reduction using PCA Exploratory Data Analysis Feature Selection

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Advancement in Decision Trees: CART, C4.5, C5.0, Overfitting, Truncation and Pruning • Model Evaluation and Selection, Comparing Classifiers Based on Cost– Benefit and ROC Curves, Techniques to Improve Classification Accuracy, bias, variance • Introducing Ensemble Methods, Bagging, Boosting and Ada-Boost, • Random Forests, Improving Classification Accuracy of Class-Imbalanced Data • Lazy Learners: Nearest Neighbour Classification

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• Unsupervised learning • K Means • Hierarchical clustering, K-Medoids and density-based clustering, • Measures of quality of clustering. BIRCH, Fuzzy Clusters • Gaussian Mixtures as Soft K-means Clustering • Vector Quantization • Expectation-Maximization (EM) algorithm for unsupervised learning

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Advanced Machine Learning Models • Regression: Multi-variable regression; Model evaluation; Least squares regression; Regularization; LASSO; Applications of regression, Overfitting and Underfitting • Hidden Markov Models (HMM) • Sequence classification using HMM; Conditional random fields; Applications of sequence classification such as part-of-speech tagging

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Trends in Machine Learning • Bayesian Belief Networks, Concepts and Mechanisms • Genetic Algorithms • Reinforcement Learning • Active Learning • Transfer Learning

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Analog Transmission: Analog-to-Analog conversion, Digital-to-Analog conversion, Digital Transmission: Digital-to-Digital conversion (line coding, block coding, scrambling), Analog-to-Digital conversion (Pulse Code Modulation, Delta Modulation) Types of Networks, Network Architectures, Network Topologies, Transmission media’s, Networking devices, OSI Model, TCP/IP Reference Model, Ethernet standards.

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Data Link Layer Services, Types of errors, Block coding, Error Control: Cyclic Redundancy Check (CRC) Code, Hamming Code, Checksum, sliding window Protocols: Selective Repeat (SR) & Go Back N (GBN), Channel allocation, Multiple Access Protocols: ALOHA, CSMA/CD, CSMA/CA, Ethernet Frame forma

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Services, Internet Protocol: Ipv4 & Ipv6, Classful Addressing, Classless Addressing, CIDR, Subnetting, NAT, ARP, RARP ICMP, Routing Algorithms: Distance-Vector (DV) Routing, Link State (LS) Routing, Routing in Internet: RIP, OSPF, BGP

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Services, Multiplexing, demultiplexing. Sockets, UDP, RTP, TCP: Services, Features, Segment, TCP Connection (Three-Way Handshake), Flow control and buffering, Silly window syndrome, Congestion Control. Congestion Control (Leaky Bucket, Token Bucket), Quality of Service (QoS)

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Dynamic Host Control Protocol (DHCP), Hypertext Transfer Protocol (HTTP), FTP, TELNET, SMTP: POP3, IMAP, MIME, Domain Name System (DNS), SNMP.

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