Tutors

Innomatics Research Labs

PROGRAM OVERVIEW

CURRICULUM

  Quiz

  • Introduction to Statistics
  • Descriptive Statistics
  • Probability Distributions

  Welcome to the Course

  • Innomatics Discord Community Joining Link
  • Zoom Mentoring Links

  Core Python

  • Anaconda Installation Processor for Python and Jupyter Notebook IDE
  • Intro to Data Science
  • Intro to Python and Jupyter Notebook
  • Intro to Python and Jupyter Class file
  • Operators, Variables and Datatypes
  • Python Operators Class Files
  • Strings Class File
  • Strings Video
  • Strings - II and LIST
  • Strings File Updated Class File
  • List Class File
  • Sets and Tuple
  • Tuples Video-1
  • Tuples video-2
  • Sets and Dictionaries class files
  • Sets and Dictionaries video
  • Operators and Conditional statements
  • Operators and conditional Statements Video
  • For Loops
  • Introduction to For loops Video
  • For Loops Class File - II
  • For Loops - II video
  • Excercises on Dictionary and Loops
  • Excercises on Dictionary and Loops Video
  • Loops Revision File
  • Python Modules
  • Intro to Functions
  • Map, Filter and Reduce

  Assignments

  • Strings Assignment
  • List and Tuple Assignment
  • Sets and Dictionaries Assignment
  • Conditional Statements Assignment
  • Telephone Directory
  • Functions
  • NumPy Assignment
  • Pandas Assignment
  • Data Visualization Assignment
  • Advanced Data VIsualization Assignment
  • Probability Assignment
  • Stats - EDA Assignment
  • ML - Linear Regression
  • ML - Logistic Regression

  Projects

  • Web Scraping Class File
  • Regular Expressions
  • Web Scraping - II with EDA
  • Sample PPT Template
  • Web Scraping Project Final Submissions
  • Portfolio
  • Telephone Directory Using Flask
  • CRUD Operations using Flask
  • ML - Regression Concrete Strength Prediction
  • ML Classification - Churn Analysis (Data Preparation and Model Building)

  Data Analysis - Python

  • Numpy-I
  • Numpy-II
  • Pandas Series
  • Pandas DataFrame
  • Pandas Operations
  • Missing value Treatment
  • Pandas Date and Time
  • Pandas Exercise
  • Uni variate Analysis
  • Bivariate Analysis
  • Advanced EDA
  • File handling and Exception handling
  • Class and Objects
  • Regular Expressions - 1
  • Plots Material

  SQL

  • MySQL Installation Step by Step Procedure
  • MySql Installation Processor File
  • Data its types and Introduction to SQL
  • SQL - II Basics and First Command
  • SQL - III Lab Session
  • SQL - IV Lab
  • SQL - V Lab

  Tableau Module

  • Tableau Installation Procedure Files
  • Day 1 Tableau File
  • Tableau - 1 Introduction
  • Super Store Dataset
  • Tableau - 2 Data Types Column Formatting Sorting Hierarchy Types of Files Discrete vs Continuous
  • Tableau 3 - Groupby and Filters
  • Tableau 4 - Parameter (Filter & Set) & Data Relationship
  • Tableau 5 - Rank Shapes Models Forecasting Clustering Summarization and Parameters as measures
  • Tableau Tasks (18 Excercises)
  • Tableau 6 - Functions - Number & string Actions at Worksheet Maps, Animation Pages
  • Tableau 7 - Dash board Story Board Publishing Extract Data and Charts
  • Tableau 8 - Special Charts LOD include Exclude Live Dashboard on Web Scraping Assignment

  Statistics

  • Descriptive Statistics Lab - I
  • Dispersion Lab
  • Basics of Probability
  • Probability Lab
  • Probability Lab
  • Statistics Data Types
  • Probability Distributions Lab
  • Distributions Class PDF
  • Distributions Lab - II
  • Normal Distribution Class Notes
  • CLT PDF
  • CLT Lab
  • Confidence Limits class PDF
  • Hypothesis Testing - I
  • Hypothesis Testing File - I
  • Hypothesis Testing - II
  • Hypothesis Testing - II
  • Hypothesis Testing - III
  • Chi Square Test
  • Chi Square Test Files
  • Stats Recap
  • Stats Recap PDF
  • Data Analysis

  Machine Learning

  • Intro to Machine Learning
  • Intro to ML File
  • Encoding and Coding File
  • Data Preprocessing Steps
  • Introduction_Day2
  • Day 3
  • ML Framework and Data Preparation
  • Text preprocessing and Numerical vector conversion
  • KNN
  • DataScience Lifecycle
  • IRIS KNN
  • Simple linear Regression
  • Simple Linear Regression File
  • kNN Files
  • Framework Files ML
  • Data Science LifeCycle File
  • NLP Files
  • Multiple Linear Regression Class File Notes
  • Multiple Linear Regression
  • Multple linear regression
  • Logistic Regression Theory
  • Linear Regression Assumptions and Evaluation File
  • Gradient Descent Class File
  • 30th May - Part 1 - Linear Regression Assumption and Evaluation metrics
  • 30th May - Part 2 - Linear Regression Assumption and Evaluation metrics
  • 31stMay - Part 1 - Model Output Interpretation and lab of assumptions
  • 31stMay - Part 2 - Model Output Interpretation and lab of assumptions
  • Insurance Data Set
  • Linear Regression Coefficient Class PDF
  • House pricing Dataset
  • Polynomial Regression and Model Interpretation Class Note File
  • Polynomial Regression Lab File
  • Linear Regression Lab File
  • Linear Regression Interpretation and Polynomial Regression
  • NaiveBayes
  • Naive Bayes theory
  • Naive Bayes Lab + Classification Evaluation Metrics - Confusion matrix and Other Metrics
  • Naive Bayes Class and Lab Files
  • Naive Bayes Lab Files
  • Decision Tree Theory - Part 1
  • Decision Tree Theory Part - 1
  • Performance Metrics and Naive Bayes
  • Decision Tree - Part 2
  • Decision Tree Complete Files
  • Machine Learning - Revision KNN Linear Regression Logistics and Decision Tree
  • ML Revision Till Date
  • SVM File
  • SVM
  • Logistics Regression (Maximum Likelihood MLE)
  • Logistic Regression MLE Topic PDF
  • Model Selection
  • Model Selection PDF
  • Model Selection Part 1
  • Model Selection Part 2