Fundamental Probability Concepts includes: Principles of Probability, Conditional Probability and independence, Random Variables etc…. Probability Advanced Concepts includes: Co-Distribution, Expected Value, Central Limit Theorem etc…. Basic Statistics and Random Sampling… MLE, MSE Concepts… Confidence Interval Concept… Hypothesis Tests Concepts… What is P-value?… Statistics and Linear Algebra Implementation in Python… Statistics in R…
Data Pre-Processing Concept… Labeled and Unlabeled Data… Work with Numpy and Pandas libraries (Advanced)… Work with Scikitlearn and Scipy Libraries… Data Analysis with Python… Work with Seaborn library… Overfitting and Underfitting Concepts…
Import Data into R… How to Replace Missing Values in R… Data Visualization in R… Statistical Analysis in R…
Introduction to Supervised Learning… Cross Validation Concept… Classification Algorithms: KNN, Decision Tree… Regression Concepts: Linear Regression, Polynomial Regression, Ridge…
Introduction to Unsupervised Learning… Clustering Algorithms: K-means, Hierarchical…