Tutors

Innomatics Research Labs

PROGRAM OVERVIEW

CURRICULUM

  Welcome to the Course

  • Zoom Mentoring session Links
  • Discord Community - Innomatics Link

  Python Programming

  • Intro to Data Science
  • Python basics File
  • Strings File
  • Python Basics
  • Strings
  • List and Tuple
  • Conditional Statement
  • Loops
  • Set and Dictionary
  • if else and While File
  • for loop File
  • Python Material
  • Data Structure - List Tuple Set and Dictionary Class File
  • Functions
  • File handling
  • Function Files
  • OOPS File
  • File and Exceptional handling File
  • Class and Objects

  Data Analysis Python

  • Numpy
  • Numpy - 1 Class file
  • Numpy - II
  • PandasPart2
  • Pandas Part3
  • Pandas_I_II_III materials
  • Descriptive statastics_part1
  • Descriptive statastics_visualisations
  • Descriptive statastics_visualisations_part2
  • Visualisations_part3
  • Regular Expressions
  • Webscraping
  • Visualization
  • Regex File
  • Web Scraping File
  • Webscraping_part2
  • Regex_Visualization_Webscraping

  Assignments

  • Python - List and Tuple
  • Python - String
  • Python - Set and Dictionary
  • Python - Conditional statements and loops
  • Python - Functions and Methods
  • Data Analysis - Numpy
  • Data Analysis - Pandas Assignment
  • Stats - EDA Assignment
  • Hypothesis Testing Assignment
  • ML - Linear Regression Assignment
  • ML - Logistic Regression

  Projects

  • Python - Web Scraping with EDA Project
  • Innomatics PPT Template
  • MySQL Project
  • ML - Regression Concrete Strength Prediction
  • ML - Classification Project

  Statistics

  • Measures of Central Tendency
  • Probability
  • Conditional Probability
  • Bayes Theorem
  • Bayes Theorem Refence Notes
  • Random Variable
  • Probability & Bayes Theorem Class files
  • Bernoulli and Binomial Distribution
  • Poisson, Normal and Standard Normal Distribution & CLT
  • Poisson, Normal and Standard Normal Distribution & CLT Reference Notes
  • Normal Distribution Questions
  • Central Limit Theorem
  • Confidence Interval
  • Confidence Interval - II
  • Hypothesis Testing
  • Hypothesis Testing - II
  • Hypothesis Testing - III
  • Central Limit Theorem Lab
  • Hypothesis Testing Reference Notes
  • Hypothesis Testing Lab
  • Hypothesis Testing Lab - II
  • Chi Square Test
  • ANOVA
  • ANOVA - II
  • Probability and Distribution Lab File
  • Hypothesis Testing Lab Files

  Machine Learning - Supervised Regression

  • Intro of Machine Learning
  • Math Behind ML
  • Simple Linear Regression
  • Intro to ML
  • Simple Linear Regression Class File
  • Gradient Descent
  • Linear Regression Lab Using Sklearn
  • Data Preprocessing File
  • Simple Linear Regression
  • Simple Linear Regression File
  • Linear Regression Lab - II
  • Linear Regression - I & II Lab Files
  • Multiple Linear Regression
  • Multiple Linear Regression Lab
  • Multiple Linear Regression Lab File
  • Polynomial Regression
  • Polynomial Regression FIle
  • Evolution Metrics and Bias Variance Trade off
  • Evaluation Metrics File
  • Regularization
  • Regularization File
  • Linear Regression from Scratch
  • Linear Regression from Scratch File
  • Revision of Linear Regression

  Deep Learning

  • This section has no content published in it.

  SQL and Tableau

  • SQL - 1
  • SQL Installation File
  • SQL - 2
  • SQL - 3
  • SQL - 3 File
  • SQL - 4
  • SQL - 5
  • SQL - 6
  • Python Connections Files
  • Project Discussion
  • SQL Use Case

  Interview and Placement Activities

  • Resume Building
  • Mastering LinkedIn Session for Effective Job Search
  • Python Interview Preparation Session
  • SQL Interview Preparation Session
  • Resume Building Session

  Machine Learning - Supervised Classification

  • Logistics Regression
  • Logistics Regression File
  • Logistics Regression Lab
  • Logistics Regression Lab - II & Evaluation Metrics
  • Logistics Regression Lab - II & Evaluation Metrics File
  • Evaluation Metrics - II
  • Evaluation Metrics - II File
  • KNN
  • KNN Class Notes
  • KNN Lab
  • KNN Lab File
  • Image Classification
  • Image Reorganization Lab
  • Image Reorganization Lab File
  • Decision Tree
  • Decision Tree - II
  • Decision Tree - II File
  • Decision Tree - III Theory and Lab
  • Decision Tree - II Lab
  • Decision Tree Lab
  • Ensemble Techniques
  • Ensemble Techniques Lab
  • Random Forest Lab
  • Ensmeble - II
  • Random Forest Files
  • k Means Clustering Lab
  • Clustering Files
  • Hierarchal Clustering
  • Hierarchical Clustering Files
  • SVM Files
  • SVM - I
  • SVM - II
  • SVM - III
  • SVM Class File
  • Hyper Parameter Tuning
  • Revision of ML + Evaluation Metrics Regression
  • ML Revision +Evaluation Metrics Regression
  • ML Revision - Classification Evaluation Metrics + ROC Curve + Feature Engineering
  • Feature Selction - Pearson Correlation + Forward Selection + VIF and Backwards Elimination
  • Feature Selection PDF
  • Feature Engineering - Lab
  • Project Discussion
  • ML Project Adult use case File
  • Feature Selection Lab File

  Machine Learning - Unsupervised

  • Clustering Lab
  • Clustering Files
  • Hierarchal Clustering

  Placement Assessment Section

  • Python, Data Analysis and Statistics Quiz - Interview Preparation SET - A - 31st Oct
  • Machine Learning Interview Preparation Test_Online 3rd Nov
  • Deep Learning Interview Preparation Test - 4th Nov

  Data Analysis Assessment

  • Python Data Analysis Assessment