Tutors

Innomatics Research Labs

PROGRAM OVERVIEW

CURRICULUM

  Course Took Kit (Discord and Mentoring Link)

  • Discord Innomatics Server Community Link
  • Zoom Mentoring Sessions Link
  • Intro to Data Science

  Python Programming

  • Ananconda Installation for Jupyter notebook IDE and Python
  • Functions File
  • Introduction to Python File
  • String File'
  • List and Tuple File
  • Dictionary File
  • Set File
  • Operators Conditional Statement and loops File
  • Functions and File Handling File
  • Exception handling and OOPs File
  • Basic Programming - Part 1
  • Python Programming Operators and Sting - Part 1
  • Strings - II
  • list
  • Tuple and Dictionary
  • Sets
  • Conditional Statement - If Else
  • Conditional Statement
  • Conditional Statement and While Loops
  • Functions - Lambda Map Filter Reduce
  • File Handling
  • File and Exceptional Handling
  • OOPS - I
  • OOPS - II
  • OOPS - III Part 1
  • OOPS - III Part 2
  • OOPs File

  Data Analysis Using Python

  • Intro to DA File
  • Descriptive_Stats File
  • Normal_Dist_Correlation File
  • Data Visualization_Conversions File
  • Numpy File
  • Pandas_Intro_Series_DataFrames File
  • Pandas2_Modifying and Sorting File
  • Intro to Data Science and Stats
  • Descriptive Stats - Population Sampling Data Measures and Types
  • Different Data Scales, Converting numeric data to categorical, Categorical to Numeric.
  • Descriptive Stats - Central Tendency and Measure of Dispersion
  • Measure of Dispersion - II
  • Pandas - I Pandas Introductions, Series, DataFrames, DataFrame Functionalities.
  • Data Summarization using pandas, reading, writing.
  • Pandas data Access using loc, iloc, modifying, sorting
  • Pandas Merge concat get_dummies cutqcut_append
  • Pandas5_Merge_Concat_append_cut File
  • Pandas_Groupby_Crosstab_Pivot_MultiIndexing File
  • Pandas Duplicated, Drop duplicated, datetime module of python and pandas.
  • Multi Indexing filtering, Shift, Rank, Rolling functions and Cumulative Functions
  • Pandas Duplicated, Drop duplicated, datetime module of python and pandas.
  • Numpy - I
  • Numpy - II
  • matplolib - II
  • EDA Univariate and Bivariate
  • EDA Adv Plots and Regex
  • Regex - II
  • Web Scraping - I
  • Web Scraping - II
  • Web Scraping - III

  Assignments

  • Variables and Datatypes
  • Strings
  • List and Tuples
  • Sets
  • Dictionary
  • Conditional Statements and Loops
  • Functions
  • Python - Class and Object
  • Data Analysis - Numpy
  • Data Analysis - Pandas
  • Data Analysis - Visualization

  Projects

  • SQL Project Demonstration
  • Web Scraping Project Final Submissions
  • SQL Project - MUSIC STORE DATA ANALYSIS
  • NLP - Text Processing Basics
  • Case Study - Customer Churn Prediction (Telecommunication Domain)
  • Text Data - Sentiment Analysis
  • Image Data - Recognising Handwritten Alphabets

  SQL

  • SQL - 1 Introduction to SQL and SQL Installation
  • SQL - 2 SQL DDL Commands Understanding theory
  • SQL 3 - DDL and DML Commands Lab
  • SQL 4 - String Operation and group by
  • SQL - 5_Group by and constraints File
  • SQL 6 - Constrains continue
  • SQL 7 -medical case study
  • SQL 8 - joins
  • SQL 9 - Windows Functions
  • SQL - 10 Stored Processors and Triggers

  Tableau - Recording

  • Tableau - 1 Intro to Tableau and Installation
  • Tableau 2 - grouping and sorting
  • Tableau 3 - Filter and advance filters
  • Tableau 4 - Parameters and calculated fields
  • Tableau 5 - Analytics in tableau
  • Tableau 6 - Consumer Financial complaints case study
  • Tableau 7 - Consumer Financial Complaint Case Study Part 2
  • Tableau 8 - Dashboard Creation

  Statistics

  • Descriptive Stats and Probability File
  • poisson_expo_ File
  • Random_Variables_Bernouli_Binomial
  • Normal Distribution File
  • CLT File
  • Interval Estimation File
  • Hypothesis Testing File
  • Introduction to Descriptive Statistics
  • Measure of Dispersion
  • Correlation Correlation, Percentiles, Deciles, Quartiles, IQR, Population, Sample, Data Categories
  • Importance of Probability, Introduction to Probability, Types of Probability
  • Revision of Probability, Conditional Probability, Bayes Theorem, Independent Events
  • random variables, Types of Random Variables , Bernouli , Binomial
  • Expected values, PDF, PMF, CDF, Uniform Distribution in continuous space and discrete space
  • Poisson and Exponential Distributions, Example problems
  • Normal Distribution, Empirical Rules, How to Plot Normal Distribution
  • Standard Normal Distribution, Problems on Normal Distribution, Z-tables, Transformations
  • Bootstrapping, Central Limit Theorem
  • CLT for Proportion Estimation of Population parameters point and Interval
  • Confidence Interval, Criterial Value Significance Level
  • Example on CI , T Distribution and Excel Lab
  • Chebyshev's theorem, Bias, Introduction to Hypothesis testing, Null & Alternative Hypothesis
  • Hypothesis Testing - Part 2 Type 1 & 2 Errors
  • Z-Test, T-test, p value approach, p value calculation, Example Problems.
  • Python lab of hyp testing, Chi square dist, Chi square test for independence
  • Chi Sqaured and F Distribution & ANOVA

  Machine Learning

  • 18th Mar - Intro to ML
  • 25th Mar - Data Preprocessing
  • 26th Mar - Diamond Price Prediction, Maths for ML
  • 19th Mar - Data Science Life Cycle, ML Framework
  • Intro to ML File
  • Data Science Life Cycle File
  • Data_Processing File
  • Diamon_Price File
  • 1st April - KNN Classification, Regression, Metrics Part 1
  • 1st April - KNN Classification, Regression, Metrics Part 2
  • 2nd April - Classification and Regression Metrics, NLP Bag of words, IF-IDF
  • KNN_classification_Regression_ File
  • NLP_ File
  • 9th April - Image Processing using PIL, Case Study-MNIST, car type prediction
  • 8th April - Python Implementation of BoW, TF-IDF, Building Models, Image Processing Basics
  • Image_Processing_ File
  • 15th April - Probability revision, Naive bayes Algorithm derivation, Variations of NB
  • Naive_Bayes_ File
  • 6th May - Decision Tree for classification & Regression-Pruning
  • Decision Tree for classification & Regression-Pruning File
  • 7th May - Linear Regression- SLR, MLR
  • Linear Regression- SLR, MLR File
  • 15th May - Ensemble Techniques
  • 16th May - AdaBoost, GradientBoost
  • 18th May - XGBOOST for regression, Classification, Pruning, Cover, Output Value, Similarity Score.
  • 17th May - Boosting
  • 22nd May - Catboost-2, LightGBM
  • 23rd May - Feature Engineering (Why Feature Engineering, Different ways etc)
  • 15th May - Ensemble_Techniques File
  • Gradient Boosting Trees-1, XGBOOST part 1 File
  • xgboost optimizations, Catboost - Ordered Target Encoding File
  • catboost_lightgbm File
  • Feature_Engineering_1_ File
  • 25th May - Feature Engineering-Filter Methods, Wrapper Methods, Embedded Methods, Hybrid
  • Feature_Engineering_ File
  • 26TH May - Python code for feature Selection
  • Python code for feature Selection fILE
  • 30th May - Overfitting, Under fitting, Cross validation and types, Ridge Regularization
  • Overfitting, Under fitting, Cross validation and types, Ridge Regularization File
  • 31st May - Ridge, Lasso, Class Imbalance problem, Improving Model Performance etc
  • 31st May - Ridge, Lasso, Class Imbalance problem, Improving Model Performance etc
  • 1s June -
  • HyperParameterTuning File
  • ML Case Study-1 (Credit Score classification)
  • 2nd June - ML Case Study-1 (Credit Score classification)
  • 5th June - Unsupervised Learning - Clustering
  • Unsupervised Learning, K Means
  • 6th June - Case Study - With Pipelines, Without Pipelines, SMOTE
  • Building Models using with Pipelines, without pipelines, SMOTE pipeline etc. File

  Deep Learning

  • 24th June - Intro to Deep Learning
  • Intro to Deep Learning
  • Forward Propagation, Back Propagation+Memoization
  • Forward Propagation, Back Propagation+Memoization
  • Forward Propagation, Back Propagation+Memoization Class File
  • Forward Propagation, Back Propagation+Memoization Video
  • Activation Functions
  • L1&L2 Regularization and Early Stopping
  • 8 July 2023 Batch Normalization, Weight Initialization, Tensorflow Code
  • 8 July 2023
  • 9 July 2023 Tensorflow-2, Computer Vision, Opencv-1
  • 9 July 2023 Tensorflow-2, Computer Vision, Opencv-1
  • 15 July 2023 OpenCV -II
  • 16 July 2023 OpenCV-III,CNN Introduction
  • 16 July 2023 OpenCV-III,CNN Introduction
  • 22 July 2023 CNN -II
  • 22 July 2023 CNN -II Notes
  • 23 July 2023 Pre Trained Models, CNN Architectures, Functional API, Transfer Learning
  • 23 July 2023 Pre Trained Models, CNN Architectures, Functional API, Transfer Learning
  • 29 July 2023 Object Detection, Image Segmentation
  • 29 July 2023 Object Detection, Image Segmentation Notes
  • 30 July 2023 Image Segmentation, Word Embeddings, AutoEncoders, RNN (LSTM, GRU)
  • 30 July 2023 Image Segmentation, Word Embeddings, AutoEncoders, RNN (LSTM, GRU) Notes
  • 5 August 2023 LSTM, GRU, Bidirectional RNN, LSTM
  • 5 August 2023 LSTM, GRU, Bidirectional RNN, LSTM Notes
  • 6 August 2023 next word prediction, RNN Types, Image Captioning
  • 6 August 2023 next word prediction, RNN Types, Image Captioning Notes
  • 12 August 2023 Named Entity Recognition, Seq2seq, Attention, Transformers, BERT
  • 12 August 2023 Named Entity Recognition, Seq2seq, Attention, Transformers, BERT Notes
  • 13 August 2023 Transformers Python code
  • 13 August 2023 Transformers Python code notes

  ML DL Projects

  • Project -1 Movie Income Prediction
  • Project - 2 MNIST Handwritten Alphabet Recognition
  • Project - 3 Sentiment Analysis
  • Project - 4 ANN ATM Project
  • Project - 5 OpenCV Haar cascade filter project
  • Project - 6 Rice Classification
  • Project - 7 Language Detection with NLP