Introduction to Data Science and AI

(67)
20 Hours

Course Outline

Module 1

1. Probability and Statistics
2. Regression
3. Binary Classificaition
4. Probabilistic Classification using Bayes Theorem
5.Multivariate Regression and Time series
     a. Multiple Regression
     b. Multicollinearily
     c. LASSO (Least Absolute Shrinkage and Selection Operator)
     d. K-Fold Cross Validation
6. Python Libraries for Data Science
     a. Pandas
     b. Numpy
     c. ScikitLearn
     d. Matplotlib
7. Hands-on Python Implementation
     a. Binary Classification
     b. Multivariate Classification
     c. Cross Validation Techniques
Module 2

1. Generalized Regression and Basic Classification
2. Linear Model for Classification
3. Understanding of Perceptron
4. Updation of Learning Rates
5. Support Vector Machines
6. Generalized Linear Models
     a. Logistic Regression
     b. Multiple Logistic Regression
     c. Poisson Regression
7. Hand-on Python Implementation
     a. Linear Model Classification using Logistic Regression
     b. Multiple Logistic Regression
     c. Poisson Regression
     d. Support Vector Machines
Module 3

1. Clustering Algorithms
     a. K-Means
     b. Mixture of Gaussians
     c. Segmentation as Clustering
     d. Hierarchical Agglomerative Clustering
     e. Agglomerative Clustering
2. Finding Similar Items
     a. Scene Completion Problem
3. Hands-on Python Implementation
     a. K-Means Algorithm
     b. Hierarchical Agglomerative Clustering

Prerequisite

1. Laptop with Internet Connectivity.
2. IDE of your choice : Recommended VS Code.
3. GitHub Account and Git.
4. Python3.
5. Dependencies : Pandas, Numpy, Scikit Learn and Keras






Aparnasri, Babu Balu, Arko Chatterjee

Aparnasri is experienced in hedge fund industry, reconciliation, process efficiency, entity reporting and accounting and currently working with data modelling, compiling and processing of data at Vel.ai Analytics and previously at D.E. Shaw Group

Babu Balu is a Technical Architect at Brainchild Technologies LLP, where he heads a team in software development and services for the Data Storage Industry. His primary focus is in Test Automation using Python. A seasoned professional who has a lot experience in the industries across verticals mentoring and nurturing teams.

Arko is a Full Stack Engineer at GAIUS Networks, where he lead the engineering team to develop powerful algorithms and webapps to empower the next 3 billion mobile users to interact, transact and monetize with local content and communities. He completed his undergrad from SRM-IST, India with research interests in Computer Vision and experienced in Full Stack and UI/UX