FAQ About 360DigiTMG

At 360DigiTMG, our Data Science course is comprehensive and covers a wide range of modules to provide students with a thorough understanding of this field. Some of the key modules included in our Data Science course typically cover topics such as: 1. Python Introduction 2. SQL 3. Data Science - Preliminaries 3a. CRISP-ML(Q) - Business & Data Understanding 3b. Data Preprocessing 3c. Exploratory Data Analytics (EDA) 3d. Feature Engineering 4. PowerBI 5. Data Mining - Unsupervised Learning 5a. Mathematical Foundations 5b. Clustering / Segmentation 5c. Dimension Reduction 5d. Association Rules 5e. Recommender Systems 5f. Network Analytics 5g. Text Mining and Natural Language Processing (NLP) 6. Data Mining - Supervised Learning 6a. Machine Learning 6b. Machine Learning Classifier Technique - Naive Bayes 6c. Machine Learning - KNN Classifier 6d. Confidence Interval 6e. Hypothesis Testing - The ‘4’ Must Know Hypothesis Tests 6f. Supervised Learning – Regression Techniques 6g. Multiple Linear Regression - Predictive Modelling 6h. Logistic Regression Binary Value Prediction, MLE 6i. Lasso and Ridge Regressions 6j. Multinomial and Ordinal Logistic Regression 6k. Advanced Regression for Count Data 6l. Kernel Method - SVM 6m. Survival Analytics 6n. Decision Tree 6o. Ensemble Techniques 7. Forecasting/Time Series 7a. Model-Driven Algorithms 7b. Data-Driven Algorithms 7c. Deep Learning for Time Series New! 8. Black Box method (ANN, CNN, RNN) 8a. Introduction to Perceptron and Multilayer Perceptron 8b. Building Blocks of Neural Network - ANN 8c. Deep Learning Primer 9. Generative AI & Transformers New! 10. Prompt Engineering New!