Tutors

Innomatics Research Labs

PROGRAM OVERVIEW

CURRICULUM

  Welcome to the Course

  • Zoom Mentoring session Links
  • Discord Community - Innomatics Link

  Python Programming

  • Intro to Python File
  • Python Basic Data Structures and inbuilt functions
  • Intro to Data Science
  • Intro to Python
  • Data Structure - List and Tuple
  • Data Structure - Dictionary Set and Strings
  • Conditional Statement and Loops - I
  • Conditional Statement and Loops - II
  • Conditional Statements and Loops File
  • Function and Exceptional handling
  • Functions
  • Exceptional handling and Recap and Quiz
  • Class and Objects

  Data Analysis - Python

  • Numpy
  • File Handling and Time & date
  • Numpy Files
  • Pandas - I
  • Pandas - II
  • Pandas - III
  • Pandas Files
  • Pandas - IV
  • Pandas Complete Files
  • Visualization - I
  • Visualization - II
  • Regular Expression
  • Web Scraping
  • Visualization Files
  • Regular Expression Files
  • Web Scraping File
  • Project Discussion

  Assignments

  • Python - List and Tuple
  • Python - String
  • Python - Sets and Dictionary
  • Python - Conditional Statement and Loops
  • Python - Functions and Methods
  • Python - Functions and Methods
  • Python - Class and Object
  • Python - Numpy
  • Data Analysis - Pandas
  • Data Visualization
  • Stats - EDA Assignment
  • Hypothesis Testing Assignment
  • ML - Linear Regression Assignment

  Projects

  • Web Scraping With EDA
  • PPT Innomatics Tamplate
  • MySQL Project
  • ML - Regression Concrete Strength Prediction
  • ML - Classification Project

  Statistics

  • Measures of Central Tendency
  • Probability
  • Conditional Probability
  • Bayes Theorem
  • Bayes Theorem Reference 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 Files
  • Hypothesis Testing Lab Files

  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

  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

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  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
  • ML - Logistic Regression
  • Image Reorganization Lab
  • Image Reorganization Lab File
  • Decision Tree
  • Decision Tree - II
  • Decision Tree - II
  • Decision Tree - III Theory and Lab
  • Decision Tree - II Lab
  • Decision Tree Lab
  • Ensemble Techniques
  • Ensemble Techniques Lab
  • Random Forest Lab
  • 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 - 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

  Machine Learning - Unsupervised

  • Clustering Lab
  • Clustering Files
  • Hierarchal Clustering
  • k Means Clustering Lab

  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