Data Science

Why is Data Science important Very little/none textbooks/courses covering the discipline as a whole Compare to Software Engineering/Compute Science during 70-80sof the last century Data Science is what data scientists do Why data science and data scientists are needed? Development of enabling technology Raising Expectations from customers

- Next batch: 15 Sep, 2018
- 70 hrs
- 8 weekends (Sat & Sun)

About the Course

Introduction to Data Science

Introduction to Machine Learning

Python Basics

Classification

Regression

Clustering

Recommender Systems

Titanic Challenge – Kaggle

Loading the Data, doing the Feature Engineering, Building some Data Models & Validating it

Introduction to Data

Data Science- Connection with AI

Need for AI

The Various Forms of Data

BigData NLP

SN

DM

IR

RL

ML mathematical definition

Types of ML

Supervised, Unsupervised and Reinforcement

Classification and Regression

Training Data and Test Data

Underfitting and Overfitting(Bias and Variance tradeoff)

Accuracy, Precision, Recall, F Measure, ROC curve

Feature Selection, ChiSquared test

Introduction to Python

List

Tuples

Arrays

Functions

Modules

Classes and Objects

Advanced Python concepts

Conditional Probability

Eucledian distance

Cosine similarity

Pearson Correlation

K- Nearest Neighbors

Naïve Bayesian- Discrete and Continous

Decision Trees

Introduction to Random Forest

Neural Networks

Gradient Descent Learning

Types of Functions

Perceptron

Multilayer Perceptron

Support Vector Machines

Bagging and Boasting

SemiSupervised(Self Training)

Linear Regression

Nature of Linear function

Nature of Non-Linear Function

Logistic Regression

Centroids Introduction

K-means clustering

K-mediods clustering

Hierarchial Clustering - Agglomerative and Divisive

Spectral Clustering Introduction and its Applications

PCA, LDA and Factor Analysis

Content Based and Colloborative Filtering

Cold Start problem

Black Sheep

Colloborative Filtering using KNN

Pearson Correlation

Matrix Factorization

Introduction to MDP

Bandit algorithm to solve Recommender Systems

Loading the Data, doing the Feature Engineering, Building some Data Models & Validating it

Trainer details

Cibe Sridharan

MS & BE from IIT Madras | Data Scientist | Delivered trainings to 50+ professionals since 2015 | Conducted multiple MeetUPs on Machine Learning and Artificial Intelligence

© 2013 BigDataHub.org. All rights reserved