Description :
Module 1: Python Basics: It will help learn the tool, Python to be used for working with data
Module 2: Python NUMPY Library: It is used to perform a wide variety of mathematical operations on arrays
Module 3: Python PANDAS Library: It is used for data manipulation, data cleaning, data analysis
Module 4: Python MATPLOTLIB Library: Data Visualization part 1
Module 5: Python SEABORN Library: Data Visualization part 2
Module 6: Basic Statistics: For business analysis
Module 7: Advance Statistics: For business analysis
Module 8: Machine Learning
Module 9: Supervised Machine Learning: Linear Regression (Solve business problems where we have to predict a value)
Module 10: Supervised Machine Learning: Logistic Regression (Used for binary classification business problems)
Module 11: Supervised Machine Learning: Decision Tress (Used for multi-class classification business problems & regression business problems)
Module 12: Supervised Machine Learning: Ensemble (Used for multi-class classification business problems & regression business problems)
Module 13: Supervised Machine Learning: KNN (Used for multi-class classification business problems & regression business problems)
Module 14: Unsupervised Machine Learning: Clustering (Used for segmenting data points into different groups)
Module 15: Unsupervised Machine Learning: PCA (Used for segmenting data points into different groups)
Module 16: Unsupervised Machine Learning: Isolation Forest (Used for anomaly detection business problems)
Module 17: Time Series Forecasting: Used for inventory planning or forecasting business problems
Module 18: Text Analytics: Used for text mining business problems working with unstructured data
Module 19: AI: Deep Learning, Keras
Module 20: Model Deployment: Using model for predicting output on new input values
Module 21: Power BI: Data Visualization
Module 22: Generative AI
Module 23: Project
