Business Intelligence using Power BI,

Module I

Learn the python fundamentals to work with data using data libraries such as NumPy and Pandas for data analysis process and explore the concepts of SQL for data analysis.

Learn the fundamentals of Machine Learning, get acquainted with supervised, unsupervised and reinforcement learnings algorithms, apply machine learning algorithms on large datasets for exploratory data analysis. required to get meaningful insights from data.
• Machine Learning Vs Deep Learning
• Types of Machine Learning Algorithms – Supervised, Unsupervised, reinforcement.
• Classification
• Regression
• Clustering
• Dimensionality reduction

• Maths Behind Decision Tree
• Using Decision Tree classifier from Scikit Learn
• Building your own Decision Tree Classifier
• Hyper Parameter Tuning
• Implementation of Decision Tree Classifier on a Kaggle Dataset

• Introduction to Bagging
• Maths behind Random Forest
• Using Random Forest classifier from Scikit learn
• Building your own Random Forest
• Hyper Parameter Tuning & Feature Engineering
• Improving Accuracy and Implementation of Random
Forest on a Kaggle Dataset