BCOM112 Digital Technologies for Commerce (Basics of AI & ML) GGSIPU NEP 2025-26 2nd Semester Notes

Unit 1 [Book]
AI: Definitions, History, and Scope	VIEW
ML: Definitions, Relation to AI	VIEW
Key differences between AI and ML	VIEW
Types of ML:
Supervised Learning	VIEW
Unsupervised Learning	VIEW
Reinforcement Learning	VIEW
Applications of AI and ML: Real-world use cases (e.g., Healthcare, Finance, Autonomous Vehicles)	VIEW
Ethical Concerns in AI: Bias, Fairness, Privacy, and Accountability	VIEW
Future of AI	VIEW
Emerging Trends:
Generative AI	VIEW
AI in Robotics	VIEW

Unit 2 [Book]
Understanding Data, Types of Data (Structured, Unstructured), Datasets, and Features	VIEW
Data Pre-processing	VIEW
Handling Missing Data	VIEW
Normalization	VIEW
Data Scaling	VIEW
Encoding Categorical Variables	VIEW
Exploratory Data Analysis (EDA)	VIEW
Visualizing Data	VIEW
Summarizing Data	VIEW

Unit 3 [Book]
Regression: Linear Regression	VIEW
Logistic Regression	VIEW
Cognitive Learning: Information Based, Similarity based, Probability based, Error based	VIEW
Model Evaluation: Train-test split, Accuracy, Precision, Recall, F1-score, ROC-AUC curve	VIEW
Clustering: K-Means, Applications: Customer segmentation, Anomaly detection	VIEW

Unit 4 [Book]
Introduction to Neural Networks: Perceptron’s, Activation Functions, Layers	VIEW
Deep Learning Basics	VIEW
Overview of Convolutional Neural Networks (CNNs)	VIEW
Recurrent Neural Networks (RNNs), Applications	VIEW
Image recognition	VIEW
Natural Language Processing	VIEW