AI 캠퍼스 -

Syllabus

인공지능개론
Orientation Introduction to AI Subfields of AI Intelligent System Search and Optimization Big Data Data Mining Mid-term Exam	Machine Learning and Data Machine Learning Algorithms Artificial Neural Networks Computer Vision Natural Langauge Processing Game-Playing Agent Automated Machine Learning Final Exam
Orientation Introduction to AI Subfields of AI Intelligent System Search and Optimization Big Data Data Mining Mid-term Exam Machine Learning and Data Machine Learning Algorithms Artificial Neural Networks Computer Vision Natural Langauge Processing Game-Playing Agent Automated Machine Learning Final Exam

선형대수학
Linear Equations and Matrices Solving a linear system of equations Application examples Properties of determinant Determinats from a computational point of view Schwartz inequality Lines and Plans Mid-term Exam	Real vector spaces Linear combinations Homogenoues system Transition matrix Orthogonal complements Eigenvalues and Eigenvectors Least square Final
Linear Equations and Matrices Solving a linear system of equations Application examples Properties of determinant Determinats from a computational point of view Schwartz inequality Lines and Plans Mid-term Exam Real vector spaces Linear combinations Homogenoues system Transition matrix Orthogonal complements Eigenvalues and Eigenvectors Least square Final

인공지능설계
Orientation Flowchart Program Design Data Design Algorithm Design Intelligence Design Intelligent System Mid-term Exam	Top-Down Decomposition Data Flow Diagram with ADT Program Flowchart & Pseudocode Finite State Machine Markov Chain Special Lecture I Special Lecture II Final Exam
Orientation Flowchart Program Design Data Design Algorithm Design Intelligence Design Intelligent System Mid-term Exam Top-Down Decomposition Data Flow Diagram with ADT Program Flowchart & Pseudocode Finite State Machine Markov Chain Special Lecture I Special Lecture II Final Exam

인공지능수학
Vectors Linear Functions Norm and Distance Linear Independence Matrices Linear Equations Matrix Multiplication	Matrix Inverses Least Squares Least Squares Data Fitting Least Squares Classification Multi-objective Least Squares Constrained Least Squares dummy
Vectors Linear Functions Norm and Distance Linear Independence Matrices Linear Equations Matrix Multiplication Matrix Inverses Least Squares Least Squares Data Fitting Least Squares Classification Multi-objective Least Squares Constrained Least Squares dummy

데이터베이스설계
Orientation Introduction to DB Design Architecture and Classification Conceptual Data Modeling (1) Conceptual Data Modeling (2) Data Organization Legacy Databases Mid-term Exam	Relational Databases (1) Relational Databases (2) Structured Query Language (1) Structured Query Language (2) NoSQL Databases (1) NoSQL Databases (2) Big Data Final Exam
Orientation Introduction to DB Design Architecture and Classification Conceptual Data Modeling (1) Conceptual Data Modeling (2) Data Organization Legacy Databases Mid-term Exam Relational Databases (1) Relational Databases (2) Structured Query Language (1) Structured Query Language (2) NoSQL Databases (1) NoSQL Databases (2) Big Data Final Exam

기계학습
Introduction to Machine Learning Supervised Learning Unsupervised Learning Linear Regression Logistic Regression Regularization Neural Networks - Representation	Neural Networks - Cost Function Neural Networks - Backpropagation Neural Networks - Initialization Support Vector Machine K-means Clustering Principal Component Analysis dummy
Introduction to Machine Learning Supervised Learning Unsupervised Learning Linear Regression Logistic Regression Regularization Neural Networks - Representation Neural Networks - Cost Function Neural Networks - Backpropagation Neural Networks - Initialization Support Vector Machine K-means Clustering Principal Component Analysis dummy

빅데이터
Basic Statistics Relationships and Representations Graph Database Introduction to Spark Spark Data structure Language Processing with Spark 1 Language Processing with Spark 2 Mid-term Exam	Analysis of Streaming Data with Spark 1 Analysis of Streaming Data with Spark 2 Using Spark MLlib 1 Using Spark MLlib 2 Spark 3.0 Spark 3.0 Deep learning with Spark Final Exam
Basic Statistics Relationships and Representations Graph Database Introduction to Spark Spark Data structure Language Processing with Spark 1 Language Processing with Spark 2 Mid-term Exam Analysis of Streaming Data with Spark 1 Analysis of Streaming Data with Spark 2 Using Spark MLlib 1 Using Spark MLlib 2 Spark 3.0 Spark 3.0 Deep learning with Spark Final Exam

휴리스틱알고리즘
Orientation Intelligent Agents Exhaustive Tree-based Search Search Strategy Admissible Heuristic & Best First Search A* Search & Priority Queue Greedy Search Mid-term Exam	TSP Modeling Hill Climbing Algorithm Stochastic Hill Climbing Simulated Annealing Tabu Search Genetic Algorithm Particle Swarm Optimization Final Exam
Orientation Intelligent Agents Exhaustive Tree-based Search Search Strategy Admissible Heuristic & Best First Search A* Search & Priority Queue Greedy Search Mid-term Exam TSP Modeling Hill Climbing Algorithm Stochastic Hill Climbing Simulated Annealing Tabu Search Genetic Algorithm Particle Swarm Optimization Final Exam

인공신경망
Introduction to Neural Networks Binary Classification Logistic Regression Gradient Descent Computation Graphs Derivatives with Computation Graphs Logistic Regression Gradient Descent Vectorization Vectorizing Logistic Regression Activation Functions	Derivative of Activation Functions Gradient Descent for Neural Networks Backpropagation Random Initialization Deep Neural Networks Forward and Backward Propagation Convolution Stride Padding Data Augmentation
Introduction to Neural Networks Binary Classification Logistic Regression Gradient Descent Computation Graphs Derivatives with Computation Graphs Logistic Regression Gradient Descent Vectorization Vectorizing Logistic Regression Activation Functions Derivative of Activation Functions Gradient Descent for Neural Networks Backpropagation Random Initialization Deep Neural Networks Forward and Backward Propagation Convolution Stride Padding Data Augmentation

자연어처리
Introduction to NLP Word Vectors 1 Word Vectors 2 Generative Process Topic Modeling 1 Topic Modeling 2 Word2Vec Mid-term	Neural Networks Introduction to TensorFlow Dependence Parsing RNN and Language Models Machine Translation Seq2Seq and Attention Transformer Networks and CNNs Final
Introduction to NLP Word Vectors 1 Word Vectors 2 Generative Process Topic Modeling 1 Topic Modeling 2 Word2Vec Mid-term Neural Networks Introduction to TensorFlow Dependence Parsing RNN and Language Models Machine Translation Seq2Seq and Attention Transformer Networks and CNNs Final

그래프기계학습
Introduction Six degrees of separation Small-world network models Power-laws Community Detection 1 Community Detection 2 Link Prediction Mid-term	Outbreak detection Network effects and information cascade Cascading behavior in networks Diffusion in networks Influence in networks Large-scale network Analysis 1 Large-scale network Analysis 2 Final
Introduction Six degrees of separation Small-world network models Power-laws Community Detection 1 Community Detection 2 Link Prediction Mid-term Outbreak detection Network effects and information cascade Cascading behavior in networks Diffusion in networks Influence in networks Large-scale network Analysis 1 Large-scale network Analysis 2 Final

인공지능정보보안
Orientation Introduction to Cybersecurity Review on Cybersecurity Solutions Data Mining and Machine Learning Overview Background of ML Methods in Cybersecurity Misuse/Signature Detection Anomaly Detection Hybrid Intrusion Detection	Mid-term Exam Scan Detection DM and ML in Network Profiling Privacy-Preserving Data Mining DM and ML in PPDM Cyber Threats Challenges in AI Cybersecurity Final Exam
Orientation Introduction to Cybersecurity Review on Cybersecurity Solutions Data Mining and Machine Learning Overview Background of ML Methods in Cybersecurity Misuse/Signature Detection Anomaly Detection Hybrid Intrusion Detection Mid-term Exam Scan Detection DM and ML in Network Profiling Privacy-Preserving Data Mining DM and ML in PPDM Cyber Threats Challenges in AI Cybersecurity Final Exam