Data Science & ML for Python-Python & Data Science Made Easy

Beginners in Python & R for Data Science: Introduction to Data science and Practical applications of Data Science and ML

Ratings 4.30 / 5.00

Data Science & ML for Python-Python & Data Science Made Easy

What You Will Learn!

Python & R programming for Structured data/ tables.
Python in demand packages used by Data Scientist and Machine Learning professionals.
Basic, Inferential and Advanced Statistics
Concept of Linear and Logistic Regression implementing with Python code
Machine Learning (ML) Algorithms concepts with Python code
ML Algorithms - Support Vector Machine
Machine Learning Algorithms. - K nearest neighbors
Practical Application of Data Science and Machine Learning in Healthcare and Real estate Industry
An approach and outlook a Data Scientist and ML professional should adopt while solving business problems in real life
Engaging Course with Multiple choice questions for Students towards end of each section for Knowledge tests
Practical & Comprehensive Assignment with Guidelines explaining challenges faced by DS/ML professional and how to deal with such roadblocks.

Description

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