This course is for Aspirant Data Scientists, Business/Data Analyst, Machine Learning & AI professionals planning to ignite their career/ enhance Knowledge in niche technologies like Python and R. You will learn with this program:
Basics of Python, marketability and importance
Understanding most of python programming from scratch to handle structured data inclusive of concepts like OOP, Creating python objects like list, tuple, set, dictionary etc; Creating numpy arrays, ,Creating tables/ data frames, wrangling data, creating new columns etc.
Various In demand Python packages are covered like sklearn, sklearn.linear model etc.; NumPy, pandas, scipy etc.
R packages are discussed to name few of them are dplyr, MASS etc.
Basics of Statistics – Understanding of Measures of Central Tendency, Quartiles, standard deviation, variance etc.
Types of variables
Advanced/ Inferential Statistics – Concept of probability with frequency distribution from scratch, concepts like Normal distribution, Population and sample
Statistical Algorithms to predict price of houses with Linear Regression
Statistical Algorithms to predict patient suffering from Malignant or Benign Cancer with Logistic Regression
Machine learning algorithms like SVM, KNN
Implementation of Machine learning (SVM, KNN) and Statistical Algorithms (Linear/ Logistic Regression) with Python programming code
Specification: Data Science & ML for Python-Python & Data Science Made Easy