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
Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.
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