Data Science Immersive Bootcamp Program - Flex
Welcome to the Data Science Immersive Bootcamp Program - a job guaranteed training program. You will get access to learning modules in this course along with all the other features such as on-demand 1:1 mentorship, weekly doubt clearing sessions and placement services.
Highlights of the Program
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100% Job Guarantee*
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Learning Modules with flexible learning
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On Demand 1:1 Mentorships with Industry Practitioners
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12+ Tools
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20+ Projects
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* For 100% Job Guarantee Terms and Conditions click here
 
Course curriculum
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            1
Bootcamp Weekly Doubt Clearing Session
- Week 1 - Bootcamp Weekly Doubt Clearing Session_31_Dec_22
 - Week 2 - Bootcamp Weekly Doubt Clearing Session_07_Jan_23
 - Week 3 - Bootcamp Doubt Clearing Session_14_Jan23
 - Week 4 - Bootcamp Doubt Clearing Session_21_Jan23
 - Week 5 - Bootcamp Doubt Clearing Session Batch 2_28_Jan23
 - Week 6 - Bootcamp Doubt Clearing Session Batch 2_04_Feb_23
 - Week 7 - Bootcamp Doubt Clearing Session Batch 2_18_Feb_23
 - Week 8 - Bootcamp Doubt Clearing Session Batch 2_25_Feb_23 - Part 1
 - Week 8 - Bootcamp Doubt Clearing Session Batch 2_25_Feb_23 - Part 2
 - Week 9 - Bootcamp Doubt Clearing Session Batch 2_04_Mar_23
 - Week 10 - Bootcamp Doubt Clearing Session Batch 2_11_Mar_23
 
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            2
Live Sessions
- 1. Session on PowerBI_11_Feb_23
 - 2. Power BI Session_12_Feb_23
 
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            3
Welcome To Bootcamp
- Bootcamp Vision and Ideology
 - Introduction to Bootcamp Flex
 - How will your journey look like?
 - Job Guarantee and Placement Services
 
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            4
Week 1 - Excel
- Introduction FREE PREVIEW
 - Course Overview FREE PREVIEW
 - Excel Installation FREE PREVIEW
 - Practice Datasets
 - Excel Interface
 - Keyboard shortcuts
 - Setting Printing Area
 - Excel Basics Exercise
 - Excel Bonus
 - Excel Basic Formatting
 - Basic Formating Exercise
 - Select, Cut, Copy, Paste
 - Autofill, Find and Search
 - Insert & Delete
 - Auto Fill Exercise
 - Sheet Operations
 - Sheet Operations Exercise
 - Getting Started with Excel Formulas
 - Referencing
 - Referencing Exercise
 - Paste Special & Format Painter
 - Copy Paste function Exercise
 - DateTime Function
 - Date Time Exercise
 - Left,Right,Mid,Len,Concatenate
 - TEXTJOIN
 - Find & Search
 - Find & Search Exercise
 - Replace & Substitute
 - Text and Value
 - Sum, Product, Mod, Sqrt, Fact
 - Round, RoundUp, Rounddown, SumIFS
 - MAXIFS
 - MINIFS
 - Mathematical Function Exercise
 - Present Value and Future Value
 - NPV and IRR
 - Financial Functions in Excel
 - Financial Function Exercise
 - Vlookup and Hlookup
 - Match
 - Index
 - Lookup Funciton Exercise
 - AND, OR, NOT, ISERROR, ISNUMBER, ISBLANK, ISTEST
 - IF, IFERROR
 - IFS
 - Logical Function Exercise
 - Hide & Unhide
 - Weekly Doubt Clearing Session
 
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            5
Week 2 - Excel
- Week-2: Introduction
 - Count, Counta, Countblank, Countifs
 - Mean, Median, Mode, Std, Rank, Quartiles, Corr
 - Statistical Function Exercise
 - Sort
 - Filter
 - Sort Fillter Exercise
 - Advanced Filter
 - Filter With One Condition
 - Filter with AND and OR operators
 - Advance Filter Exercise
 - Pivot Table I
 - Pivot Table II
 - Hide and Show Grand Totals
 - Sorting Rows and Columns
 - Calculated Fields
 - Auto Width Disable
 - Difference From Previous Value
 - Make Pivot Tables Dynamic
 - Slicers
 - Timeline Slicer
 - Pivot Table Exercise
 - Getting Started with Excel Charts
 - Components of Charts
 - How to Create a Chart
 - Column Chart in Excel
 - Bar Chart in Excel
 - Line Chart in Excel
 - Area Chart in Excel
 - Pie Chart in Excel
 - Scatter Chart in Excel
 - Data Visualisation Exercise
 - Bubble Chart in Excel
 - Dual Axis Chart in Excel
 - How to Choose Charts
 - Sparklines in Excel
 - Waterfall Chart in Excel
 - Advance Charts Exercise
 - Highlight Cells Rules
 - Top-Bottom Rules, Multiple Cells And Heatmaps
 - Duplicate and Unique Values
 - Unique Function
 - Unique with Filter
 - Case Sensitivity of Unique Function
 - Unique With All Parameters
 - What Is Spill
 - Goal-Seek and Solver
 - Scenario Manager
 - Data Tables
 - What IF Exercise
 - Data Validation
 - Data Validation Exercise
 - Protecting Cell, Sheet, Workbook
 - Data Validation II Exercise
 - Hyperlink
 - Hyperlink Exercise
 - Text to Column
 - Excel vs. Google Sheets
 - Understanding the Problem Statement
 - Simulation Sample Sheet
 - A Look at the Data
 - Formulating the Framework - Business Understanding
 - Breaking Down the Framework
 - Yearly Business Prediction
 - Pre-Requisite for the Next Lesson
 - Month-Wise Business Forecast
 - Adding Flexibility to our Simulation
 - Performing Simulation in Excel!
 - Simulation Assignment
 - Weekly Doubt Clearing Session
 
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            6
Week 3 - Power BI
- Introduction to the course
 - Course Handout
 - What is Business Intelligence?
 - Components of BI
 - Quiz: Business Intelligence
 - What is Power BI?
 - Installation of Power BI
 - Introduction to Power BI Interface
 - Understanding the problem statement
 - Importing Data in Power BI
 - Data View and Formatting the Columns
 - Building your first Power BI Report
 - Chart Formatting and Other Visuals
 - Uploading Reports to Power BI Service
 - Quiz: Power BI Basics
 - What is Data Modeling?
 - Relationships and Cardinality
 - Creating Calculated Columns
 - Building Reports with Multiple Tables
 - Introduction to Measures
 - Creating our first Measure
 - Using Measures to perform row-by-row operations
 - CALCULATE Function to create Measures
 - Time Intelligence Functions
 - Creating Reports with Measures
 - Quiz: DAX
 - Filters in Power BI Reports
 - Hierarchy and Drill modes
 - Quiz: Filter and Slicers
 - Introduction to Parameters
 - Parameters in Power BI
 - Data Storytelling
 - Shapes and Buttons
 - Managing Roles and RLS
 - Power BI Gateway for Data Refresh
 
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            7
Week 4 - Power BI
- Introduction to Power Query
 - Cleaning Data with Power Query - Part I
 - Cleaning Data with Power Query - Part II
 - Case Study 1 - Using Power Query to Manipulate Data
 - Case Study 2 - Transpose, Pivot and Unpivot
 - Case Study 3 - Split Column
 - Grouping
 - Forecasting
 - Use of Scatter Plot
 - How to choose Correct Visuals
 - Drill through
 - Conditional Formatting
 - Report Creation
 - Basics of Power BI Cloud
 - Are my top 5 customers profitable?
 - West vs East
 - Same Period Last Year Analysis
 - Assessment (Project)
 - Capstone Project
 
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Week 5 - SQL
- Course Overview
 - Course Handout
 - Week-5: Introduction
 - Why do we need databases
 - What is a database
 - Some properties of a good Database
 - Types of Databases
 - How data is Stored in Relational Databases
 - ACID Properties of Relational Databases
 - Companies using MySQL
 - Quiz - Introduction to Databases
 - Architecture - Client and Server
 - MySQL Distributions
 - Local Installation on Mac
 - Local Installation on Linux
 - Local Installation on Windows
 - Quiz - Installing MySQL
 - Getting Started with SQL
 - What is SQL
 - Connecting to MySQL on Windows
 - Connecting to MySQL on Linux
 - Connecting to MySQL on Mac
 - Exploring Databases
 - Creating a Table
 - Datatypes in MySQL
 - Describe Command
 - Describing Tables
 - Insert Command
 - Inserting Records
 - Retrieving Records
 - NULL vs NOT NULL
 - Dealing with NULL values
 - Quiz - Getting Started with SQL
 - Update Command
 - Updating Records
 - Delete Command
 - Deleting Records
 - Alter Command
 - Altering Table Structure
 - Drop Table
 - Dropping Table
 - Quiz - Modifying Table Structure
 - Importing data from CSV to MySQL
 - Counting Records
 - Aggregation Functions
 - Extreme Values Identification
 - Quiz - Basic Querying 1
 - Slicing Data
 - Limiting Data
 - Sorting Data
 - Quiz - Basic Querying 2
 - Pattern Matching
 - Quiz - Basic Querying 3
 - Grouping Records
 - Filtering in Groups
 - Quiz - Basic Querying 4
 - Exporting data from MySQL to CSV
 - Backing up Databases
 - Restoring Databases
 - Importing and Exporting Datasets Troubleshooting Guide
 - Quiz - Importing and Exporting data in MySQL
 - Description Analytics of FIFA 19 Players
 - Data Eyeballing
 - Data Dictionary
 - Questions we need answers of
 - Loading data to our MySQL table
 - Data Analysis – Simple Queries
 - Data Analysis – Advanced Queries
 - FIFA19 Players Dataset
 - String Concatenation
 - String Case Conversion
 - Trimming Strings
 - Extracting Substrings
 - Understanding RegEx
 - Matching String patterns with RegEx
 - Current Date and Time
 - Extracting Date and Time
 - Formatting Date and Time as Strings
 - Numeric functions
 - Conditional Flow
 - Writing Conditional Statements
 - SQL CheatSheet
 - Quiz - MySQL built-in functions
 - Why we need Subqueries
 - Analyzing data and creating table structure
 - What are Subqueries
 - Types of Subqueries
 - Implementing Subquery
 - Quiz - Subqueries
 - Weekly Doubt Clearing Session
 
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Week 6 - SQL
- Week-6: Introduction
 - What are Constraints
 - Domain Constraint
 - NOT NULL Constraint
 - DEFAULT Constraint
 - Adding NOT NULL and DEFAULT Constraints
 - UNIQUE Constraint
 - CHECK Constraint
 - Adding UNIQUE and CHECK Constraints
 - Key Constraint
 - Implementing KEYS in SQL
 - Quiz - Constraints in SQL
 - Working with multiple tables
 - What is Foreign Key
 - Types of Relationships
 - Quiz - Working with Multiple Tables
 - Movie TIcket Project Dataset
 - Joins Overview
 - Inner Join
 - Implementing Inner Join
 - Left Join
 - Implementing Left Join
 - Right Join
 - Implementing Right Join
 - UNION Clause
 - Full Outer Join
 - Implementing Full Outer Join
 - Cross Join
 - Implementing Cross Join
 - Self Join
 - Implementing Self Join
 - Multiple Tables with Sub-queries
 - Quiz - Joins
 - Assignment
 
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Week 7 - Python
- Overview of Machine Learning / Data Science FREE PREVIEW
 - Common Terminology used in Data Science FREE PREVIEW
 - Applications of Data Science FREE PREVIEW
 - Installation steps for Windows
 - Installation steps for Linux
 - Installation steps for Mac
 - Introduction to Python
 - Introduction to Jupyter Notebook
 - Download Python Module Handouts
 - Introduction to Variables
 - Implementing Variables in Python
 - Quiz: Operators
 - Introduction to Conditional Statements
 - Implementing Conditional Statements in Python
 - Quiz: Conditional Statements
 - Introduction to Looping Constructs
 - Implementing Loops in Python
 - Quiz: Loops in Python
 - Break, Continue and Pass Statements
 - Introduction to Data Structures
 - List and Tuple
 - Implementing List in Python
 - Quiz: Lists
 - List - Project in Python
 - Implementing Tuple in Python
 - Quiz: Tuple
 - Introduction to Sets
 - Implementing Sets in Python
 - Quiz: Sets
 - Introduction to Dictionary
 - Implementing Dictionary in Python
 - Quiz: Dictionary
 - Assignment: Data Structures
 - Introduction to String Manipulation
 - Quiz: String Manipulation
 - Introduction to Functions
 - Implementing Functions in Python
 - Quiz: Functions in Python
 - Lambda Expression
 - Quiz: Lambda Expressions
 - Recursion
 - Implementing Recursion in Python
 - Quiz: Recursion
 - Introduction to Modules
 - Modules: Intuition
 - Introduction to Packages
 - Standard Libraries in Python
 - User Defined Libraries in Python
 - Quiz: Modules, Packages and Standard Libraries
 
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Week 8 - Python
- Handling Text Files in Python
 - Quiz: Handling Text Files
 - Important Libraries for Data Science
 - Quiz: Important Libraries for Data Science
 - Basics of Numpy in Python
 - Basics of Scipy in Python
 - Quiz: Numpy and Scipy
 - Basics of Pandas in Python
 - Quiz: Pandas
 - Basics of Matplotlib in Python
 - Basics of Scikit-Learn in Python
 - Basics of Statsmodels in Python
 - Reading Data in Python
 - Reading CSV files in Python
 - Reading Big CSV Files in Python
 - Quiz: Reading CSV files in Python
 - Reading Excel & Spreadsheet files in Python
 - Quiz: Reading Excel & Spreadsheet files in Python
 - Reading JSON files in Python
 - Quiz: Reading JSON files in Python
 - Assignment: Reading Data Files in Python
 - Subsetting and Modifying Data in Python
 - Overview of Subsetting in Pandas I
 - Overview of Subsetting in Pandas II
 - Subsetting based on Position
 - Subsetting based on Label
 - Subsetting based on Value
 - Quiz: Subsetting Dataframes
 - Modifying data in Pandas
 - Quiz: Modifying Dataframes
 - Assignment: Subsetting and Modifying Pandas Dataframes
 - Preprocessing, Sorting and Aggregating Data
 - Sorting the Dataframe
 - Quiz: Sorting Dataframes
 - Concatenating Dataframes in Pandas
 - Concept of SQL-Like Joins in Pandas
 - Implementing SQL-Like Joins in Pandas
 - Quiz: Joins in Pandas
 - Aggregating and Summarizing Dataframes
 - Preprocessing Timeseries Data
 - Quiz: Preprocessing Timeseries Data
 - Assignment: Sorting and Aggregating Data in Pandas
 - Visualizing Trends & Pattern in Data
 - Basics of Matplotlib
 - Data Visualization with Matplotlib
 - Quiz: Matplotlib
 - Basics of Seaborn
 - Data Visualization with Seaborn
 - Quiz: Seaborn
 - Assignment: Visualizing Patterns and Trends in Data
 - Assignment - EMI Calculator
 
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Week 9 - Data Science Life Cycle & EDA
- 6 Steps of Machine Learning Lifecycle
 - Introduction to Predictive Modeling
 - Defining the Problem statement
 - Introduction to Hypothesis Generation
 - Performing Hypothesis generation
 - Quiz - Performing Hypothesis generation
 - List of hypothesis
 - Data Collection/Extraction
 - Quiz - Data Collection/Extraction
 - Introduction to Exploratory Data Analysis & Data Insights
 - Quiz - Introduction to Exploratory Data Analysis & Data Insights
 - Role of Statistics in EDA
 - Descriptive Statistics
 - Inferential Statistics
 - Quiz - Descriptive and Inferential Statistics
 - Introduction to dataset
 - Quiz - Introduction to dataset
 - Reading data files into python
 - Quiz - Reading data files into python
 - Different Variable Datatypes
 - Variable Identification
 - Quiz - Variable Identification
 - Probability for Data Science
 - Quiz - Probability for Data Science
 - Basic Concepts of Probability
 - Quiz - Basic Concepts of Probability
 - Axioms of Probability
 - Quiz - Axioms of Probability
 - Conditional Probability
 - Quiz - Conditional Probability
 - Data range for continuous variables
 - Central Tendencies for continuous variables
 - Spread of the data
 - Central Tendencies and Spread of the data: Implementation
 - Quiz: Central Tendencies and Spread of data
 - KDE plots for continuous variable
 - KDE plots : Implementation
 - Overview of Distributions for Continuous Variables
 - Normal Distribution
 - Normality Check
 - Skewed Distribution
 - Skewness and Kurtosis
 - Distributions for continuous variable
 - Quiz: Distribution of Continuous variables
 - Approaching Univariate Analysis
 - Approaching Univariate Analysis: Numerical Variables
 - Quiz: Univariate analysis for Continuous variables
 - Central Tendencies for categorical variables
 - Understanding Discrete Distributions
 - Discrete Distributions Demonstration
 - Performing EDA on Catagorical Variables
 - Quiz: Univariate Analysis for Categorical Variables
 
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Week 10 - EDA
- Dealing with Missing values
 - Understanding Outliers
 - Identifying Outliers in data
 - Identifying Outliers in data: Implementation
 - Quiz: Identifying Outliers in datasets
 - Quiz: Outlier treatment
 - Important Terminologies
 - Central Limit Theorem
 - CLT: Implementation
 - Quiz: Central Limit Theorem
 - Confidence Interval and Margin of error
 - Introduction to Bivariate Analysis
 - Covariance
 - Pearson Correlation
 - Spearman's Correlation & Kendall's Tau
 - Correlation versus Causation
 - Tabular and Graphical Methods
 - Performing Hypothesis generation
 - Quiz: Continuous-Continuous Variables
 - Tabular and Graphical Methods
 - Introduction to hypothesis Testing
 - P-Value
 - One Sample z-test
 - Two Sampled z-test
 - Quiz: Hypothesis Testing and Z scores
 - T-Test
 - T-Test vs Z-Test
 - Quiz: T tests
 - Performing Bivariate Analysis on Catagorical - Continuous variables
 - Tabular and Graphical Methods
 - Chi-Squared Test
 - Quiz: Chi squared tests
 - Bivariate Analysis for Categorical Categorical Variables
 - Multivariate Analysis
 - Multivariate Analysis Implementation
 - Understanding the NYC Taxi Trip Duration Problem
 - Assignment: EDA
 
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Week 11 - Basic ML
- Introduction and Overview FREE PREVIEW
 - Quiz: Introduction and Overview FREE PREVIEW
 - Preparing the Dataset FREE PREVIEW
 - Quiz: Preparing the dataset FREE PREVIEW
 - Build a Benchmark Model: Regression FREE PREVIEW
 - Quiz: Build a Benchmark Model - Regression
 - Benchmark Model: Regression Implementation
 - Quiz: Benchmark Model - Regression Implementation
 - Build a Benchmark Model: Classification
 - Quiz: Build a Benchmark Model - Classification
 - Benchmark Model: Classification Implementation
 - Quiz: Benchmark - Classification Implementation
 - Introduction to Evaluation Metrics
 - Quiz: Introduction to Evaluation Metrics
 - Confusion Matrix
 - Quiz: Confusion Matrix
 - Accuracy
 - Quiz: Accuracy
 - Alternatives of Accuracy
 - Quiz: Alternatives of Accuracy
 - Precision and Recall
 - Quiz: Precision and Recall
 - Thresholding
 - Quiz: Thresholding
 - AUC-ROC
 - Quiz: AUC-ROC
 - Log loss
 - Quiz: Log loss
 - Evaluation Metrics for Regression
 - Quiz: Evaluation Metrics for Regression
 - R2 and Adjusted R2
 - Quiz: R2 and Adjusted R2
 - Dealing with Missing Values in the Data
 - Quiz: Dealing with missing values in the data
 - Replacing Missing Values
 - Quiz: Replacing Missing values
 - Imputing Missing Values in data
 - Quiz: Imputing Missing values in data
 - Working with Categorical Variables
 - Quiz: Working with categorical data
 - Working with Outliers
 - Quiz: Working with outliers
 - Preprocessing Data for Model Building
 - Introduction to k-Nearest Neighbours FREE PREVIEW
 - Quiz: Introduction to k-Nearest Neighbours FREE PREVIEW
 - Building a kNN model
 - Quiz: Building a kNN model
 - Determining right value of k
 - Quiz: Determining right value of k
 - How to calculate the distance
 - Quiz: How to calculate the distance
 - Issue with distance based algorithms
 - Quiz: Issue with distance based algorithms
 - Introduction to sklearn
 - Implementing k-Nearest Neighbours algorithm
 - Quiz: Implementing k-Nearest Neighbours algorithm
 
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Week 12 - Basic ML
- Introduction to Overfitting and Underfitting Models
 - Quiz: Introduction to Overfitting and Underfitting Models
 - Visualizing overfitting and underfitting using knn
 - Quiz: Visualizing overfitting and underfitting using knn
 - Selecting the Right Model
 - What is Validation?
 - Quiz: What is Validation
 - Understanding Hold-Out Validation
 - Quiz: Understanding Hold-Out Validation
 - Implementing Hold-Out Validation
 - Quiz: Implementing Hold-Out Validation
 - Understanding k-fold Cross Validation
 - Implementing k-fold Cross Validation
 - Quiz: Understanding k-fold Cross Validation
 - Quiz: Implementing k-fold Cross Validation
 - Bias Variance Tradeoff
 - Quiz: Bias Variance Tradeoff
 - Introduction to Linear Models
 - Quiz: Introduction to linear model
 - Understanding Cost function
 - Quiz: Understanding Cost function
 - Understanding Gradient descent (Intuition)
 - Maths behind gradient descent
 - Convexity of cost function
 - Quiz: Convexity of Cost function
 - Quiz: Gradient Descent
 - Assumptions of Linear Regression
 - Quiz: Assumptions of linear model
 - Implementing Linear Regression
 - Generalized Linear Models
 - Quiz: Generalized Linear Models
 - Introduction to Logistic Regression
 - Quiz: Introduction to logistic regression
 - Quiz: Logistic Regression
 - Odds Ratio
 - Implementing Logistic Regression
 - Multiclass using Logistic Regression
 - Quiz: Multi-Class Logistic Regression
 - Challenges with Linear Regression
 - Quiz: Challenges with Linear regression
 - Introduction to Regularisation
 - Quiz: Introduction to Regularization
 - Implementing Regularisation
 - Coefficient estimate for ridge and lasso (Optional)
 - Predicting whether a customer will churn or not
 - Introduction to Dimensionality Reduction
 - Quiz: Introduction to Dimensionality Reduction
 - Common Dimensionality Reduction Techniques
 - Quiz: Common Dimensionality Reduction Techniques
 - Missing Value Ratio
 - Missing Value Ratio Implementation
 - Quiz: Missing Value Ratio
 - Low Variance Filter
 - Low Variance Filter Implementation
 - Quiz: Low Variance Filter
 - High Correlation Filter
 - High Correlation Filter Implementation
 - Quiz: High Correlation Filter
 - Backward Feature Elimination
 - Backward Feature Elimination Implementation
 - Quiz: Backward Feature Elimination
 - Forward Feature Selection
 - Forward Feature Selection Implementation
 - Quiz: Forward Feature Selection
 - Introduction to Decision Trees
 - Quiz: Introduction to Decision Trees
 - Purity in Decision Trees
 - Quiz: Purity in Decision Trees
 - Terminologies Related to Decision Trees
 - Quiz: Terminologies Related to Decision Trees
 - How to Select the Best Split Point in Decision Trees
 - Quiz: How to Select the Best Split Point in Decision Trees
 - Chi-Square
 - Quiz: Chi-Square
 - Information Gain
 - Quiz: Information Gain
 - Reduction in Variance
 - Quiz: Reduction in Variance
 - Optimizing Performance of Decision Trees
 - Quiz: Optimizing Performance of Decision Trees
 - Decision Tree Implementation
 - Assignment: NYC taxi trip duration prediction
 
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Week 13 - Advance ML
- Introduction to Feature Engineering
 - Quiz: Introduction to feature engineering
 - Exercise on Feature Engineering
 - Overview of the module
 - Feature Transformation
 - Quiz: Feature Transformation
 - Feature Scaling
 - Quiz: Feature Scaling
 - Feature Encoding
 - Quiz: Feature Encoding
 - Quiz: Combining Sparse classes
 - Feature Generation: Binning
 - Quiz: Feature Generation- Binning
 - Quiz: Feature Interaction
 - Generating Features: Missing Values
 - Feature Interaction
 - Frequency Encoding
 - Quiz: Frequency Encoding
 - Feature Engineering: Date Time Features
 - Implementing DateTime Features
 - Combining Sparse classes
 - Quiz: Implementing DateTime Features
 - Automated Feature Engineering : Feature Tools
 - Implementing Feature tools
 - Quiz: Implementing Feature Tools
 - Exploring the NYC dataset
 - Predicting the NYC taxi trip duration
 - Predicting the NYC taxi trip duration
 - Introduction to Text Feature Engineering
 - Quiz: Introduction to Text Feature Engineering
 - Create Basic Text Features
 - Quiz: Create Basic Text Features
 - Extract Information using Regular Expressions
 - Quiz: Extract Information using Regular Expressions
 - Learn to use Regular Expressions in Python
 - Quiz: Learn to use Regular Expressions in Python
 - Text Cleaning
 - Quiz: Text Cleaning
 - Quiz: Create Linguistic Features
 - Bag-of-Words
 - Quiz: Bag-of-Words
 - Text Pre-processing
 - Quiz: Text Pre-processing
 - TF-IDF Features
 - Quiz: TF-IDF Features
 - Word Embeddings
 - Create word2vec Features
 - Quiz: Word Embeddings
 - Create Linguistic Features
 - Introduction to Naive Bayes
 - Quiz: Introduction to Naive Bayes
 - Working of Naive Bayes
 - Conditional Probability and Bayes Theorem
 - Math Behind Naive Bayes
 - Quiz: Conditional Probability and Naive Bayes
 - Types of Naive Bayes
 - Quiz: Types of Naive Bayes
 - Implementing Naive Bayes
 - Understanding how to solve Multiclass and Multilabel Classification Problem
 - Quiz: Multiclass and Multilabel
 - Evaluation Metrics: Multi Class Classification
 - Quiz: Evaluation Metrics for Multi Class Classification
 - Understanding the Problem Statement
 - Understanding the Data
 - Building a Web Page Classifier
 - Introduction to Ensemble
 - Quiz: Introduction to Ensemble
 - Basic Ensemble Techniques
 - Quiz: Basic Ensemble Techniques
 - Implementing Basic Ensemble Techniques
 - Why Ensemble Models Work Well?
 
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Week 14 - Advance ML
- Introduction to Stacking
 - Implementing Stacking
 - Variants of Stacking
 - Implementing Variants of Stacking
 - Quiz: Variants of Stacking
 - Introduction to Blending
 - Implementation: Blending
 - Quiz: Introduction to Blending
 - Bootstrap Sampling
 - Quiz: Bootstrap Sampling
 - Introduction to Random Forest
 - Quiz: Introduction to Random Forest
 - Hyper-parameters of Random Forest
 - Quiz: Hyper-parameters of Random Forest
 - Implementing Random Forest
 - Quiz: Implementing Random forest
 - Introduction to boosting
 - Quiz: Introduction to Boosting
 - Gradient Boosting Algorithm (GBM)
 - Quiz: Gradient Boosting Algorithm
 - Math Behind GBM
 - Implementing GBM
 - Quiz: Implementing GBM
 - Extreme Gradient Boosting (XGBM)
 - Implementing XGBM
 - Quiz: Implementing XGBM
 - Quiz: Extreme Gradient Boosting
 - Adaptive Boosting
 - Implementing Adaptive Boosting
 - Quiz: Adaptive Boosting
 - Predicting the NYC Taxi Trip Duration
 - Prediction the NYC Taxi Trip Duration: Dataset
 - Introduction to Hyperparameter Tuning
 - Different Hyperparameter Tuning methods
 - Quiz: Hyperparameter Tuning
 - Implementing different Hyperparameter Tuning methods
 - Quiz: Implementing different Hyperparameter tuning
 - Understanding SVM Algorithm
 - Quiz: Support Vector Machine
 - SVM Kernel Tricks
 - Kernels and Hyperparameters in SVM
 - Quiz: Kernels and Hyperparameters in SVM
 - Implementing Support Vector Machine
 - Quiz: Kernel Tricks
 - Introduction to Images
 - Understanding the Image data
 - Quiz: Understanding the Image Data
 - Understanding transformations on Images
 - Understanding Edge Features
 - Quiz: Understanding Edge Features
 - Histogram of Oriented Features (HOG)
 - Quiz: HOG
 - Quiz: Image Features
 - Understanding the Problem Statement
 - Detecting Malaria using Blood Cell Images
 - Dataset: Malaria Detection using Blood Cell Images
 
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Week 15 - Advance ML
- Introduction to Principal Component Analysis
 - Steps to perform Principal Component Analysis
 - Quiz: Principal Component Analysis
 - Computation of the Covariance Matrix
 - Quiz: Covariance Matrix
 - Finding the Eigenvectors and Eigenvalues
 - Quiz: Finding eigenvectors and eigenvalues
 - Understanding the MNIST dataset
 - Quiz: Introduction to MNIST dataset
 - Implementing Principal Component Analysis
 - Quiz: Steps to perform PCA
 - Introduction to Factor Analysis
 - Steps to perform Factor Analysis
 - Quiz: Factor Analysis
 - Implementing Factor Analysis
 - Quiz: Implementing Factor Analysis
 - Introduction to Clustering
 - Quiz: Introduction to Clustering
 - Applications of Clustering
 - Quiz: Applications of clustering
 - Evaluation Metrics for Clustering
 - Quiz: Evaluation Metrics for Clustering
 - Understanding K-Means
 - K-Means from Scratch Implementation
 - Quiz: Understanding K-Means
 - Challenges with K-Means
 - Quiz: Challenges with K means clustering
 - How to Choose Right k-Value
 - Quiz: How to choose the right value of k
 - K-Means Implementation
 - Quiz: K-Means Implementation
 - Hierarchical Clustering
 - Implementation Hierarchical Clustering
 - Quiz: Hierarchical Clustering
 - How to Define Similarity between Clusters
 - Quiz: How to define similarity between two clusters
 - Advanced ML - Assignment
 - Capstone Project - ML
 
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Week 16 - Advance Python & Software Engineering
- Introduction to the Course
 - Course Handouts
 - Python Recap
 - Installation steps for Windows
 - Installation steps for Linux
 - Installation steps for Mac
 - Working in JupyterLab
 - Introduction to Good Programming Practices
 - Quiz: Introduction to GPP
 - Naming Conventions
 - Quiz: Naming Conventions
 - Commenting and Formatting
 - Quiz: Commenting and Formatting
 - Decomposition and Modularity
 - Quiz: Decomposition and Modularity
 - Code Formatting
 - Quiz: Code Formatting
 - Writing Docstrings
 - Quiz: Docstrings
 - What is testing?
 - Types of Bugs
 - Quiz: Types of Bugs
 - Setting up system for testing
 - Quiz: Setting up for Testing
 - Levels of testing
 - Quiz: Levels of testing
 - Testing Approaches
 - Quiz: Testing Approaches
 - Defensive Programming
 - Quiz: Defensive Programming
 - Python Typing
 - Quiz: Python Typing
 - Assertions
 - Quiz: Assertions
 - Exception Handling
 - Quiz: Exception Handling
 - Use Cases Exception Handling
 - Introduction to Standard Libraries
 - Quiz: Introduction to Python Standard Libraries
 - Itertools Library
 - Quiz: Itertools
 - Functools Library
 - Quiz: functools
 - Collections Library
 - Quiz: collections
 - Pickle Library
 - Quiz: pickle
 - Introduction to Programming Paradigms
 - Quiz: Programming Paradigms
 - Introdunction to Functional programming
 - Quiz: Introduction
 - Pure Functions
 - Quiz: Pure Functions
 - Recursion
 - Higher order Functions
 - Quiz: Higher Order Functions
 - Decorators
 - Quiz: Decorators
 - Lazy Evaluation
 - Quiz: Lazy Evaluation
 - Use Cases and Limitations of functional programming
 - Quiz: Use cases and Limitations
 
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Week 17 - Advance Python & Software Engineering
- Key Features of Object Oriented Programming
 - Quiz: Why learn OOP
 - Introduction to Object Oriented Programming
 - Quiz: Introduction to Object Oriented Programming
 - Classes and Objects
 - Quiz: Classes and Objects
 - Attributes and Types of Attributes
 - Quiz: Attributes
 - Methods and its Types
 - Quiz: Methods
 - Special Methods
 - Intuition and Introduction
 - Use cases of Inheritance
 - Quiz: Use cases of Inheritance
 - Types - Single and Multilevel Inheritance
 - Quiz: Types - Single and Multilevel
 - Types - Multiple and Hierarchical Inheritance
 - Quiz: Types - Multiple and Hierarchical
 - Introduction to Shell Commands
 - File Exploration
 - File Exploration
 - File Operations
 - File Operations
 - Running a Python File
 - Basic Shell Script Programming
 - Introduction to Gitub for Version Control
 - Quiz: Intro to version Control
 - Setting up for Github
 - Important Commands and Terminologies
 - Quiz: Important Commands and Terminologies
 - Use cases for Github
 - Quiz: Usecases for Github
 - Introduction to DataBases
 - Local Installation SQL on Linux
 - Local Installation SQL on Mac
 - Local Installation SQL on Windows
 - Connecting Python to SQL DataBases
 - Installation for MongoDB
 - Steps for MongoDB installation on Windows
 - Connecting Python to MongoDB DataBases
 
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Week 18 - AWS
- Course Overview
 - Prerequisites
 - Disclaimer
 - Course Handouts
 - Introduction to Cloud Computing
 - Key Concepts
 - Deployment Models
 - Quiz: Cloud Deployment Models
 - Service Models
 - Quiz: Service Models
 - Benefits of using AWS
 - How to create an account on AWS?
 - Learning Path FREE PREVIEW
 - Factors to Consider Before Launch
 - Regions & Availability Zones
 - Edge Points
 - Quiz: AWS Global Infrastructure
 - What is Amazon EC2?
 - Instance Types
 - Pricing Strategies
 - AWS Pricing Calculator
 - Launch Your First EC2 Instance on AWS
 - Install Jupyter Notebook on Your EC2 Instance
 - Quiz: EC2
 - Amazon Machine Images
 - How to Create AMIs?
 - Compute Services in AWS
 - Quiz: Compute Services in AWS
 - Basic Concepts of Networking Part 1
 - Basic Concepts of Networking Part 2
 - Quiz: Networking
 - Virtual Private Cloud (VPC)
 - How to Create a VPC? (Part 1)
 - How to Create a VPC? (Part 2)
 - Quiz: VPC
 - Network Access Control Lists (NACL)
 - How to Create NACLs?
 - Security Groups
 - How to Create Security Groups?
 - Quiz: NACL & Security Groups
 - Shared Responsibility Model
 - Identity & Access Management
 - How to Create IAM User Account?
 - Quiz: IAM
 - IAM Policies
 - How to Create IAM Policy?
 - Quiz: IAM Policy
 - IAM Groups
 - How to Create IAM Groups?
 - Security Services: AWS Shield & WAF
 - Security Services: KMS & AWS Inspector
 - Quiz: Security Services
 - Different Types of Storage
 - Quiz: Types of Storage
 - Amazon Elastic Block Storage (EBS)
 - How to use EBS on AWS?
 - Quiz: Elastic Block Storage
 - Amazon Elastic File System (EFS)
 - How to use EFS on AWS?
 - Quiz: Elastic File System
 - Amazon Simple Storage Service (S3)
 - How to Create S3 Bucket?
 - How to Create S3 Bucket using CLI?
 - Installation Steps: AWS Command Line Interface
 - Bucket Policy
 - S3 Storage Classes
 - Quiz: S3
 - S3 Lifecycle Policies
 - How to define S3 Lifecycle Policy?
 - IAM Roles
 - How to define IAM Roles?
 - Quiz: IAM Roles
 
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Week 19 - AWS
- Amazon Relational Database Service (RDS)
 - How to launch MySQL using RDS?
 - Connecting to MySQL
 - Quiz: Amazon RDS
 - Amazon Aurora
 - How to launch Amazon Aurora using RDS?
 - Quiz: Amazon Aurora
 - Introduction to DynamoDB
 - How to create a DynamoDB table?
 - DynamoDB using Python
 - Quiz: DynamoDB
 - Use-Cases of DynamoDB
 - What is a Data Warehouse?
 - Quiz: Data Warehouse
 - How Redshift Works?
 - Quiz: Redshift
 - Understanding Columnar Storage
 - Quiz: Columnar Storage
 - How to Create a Redshift Cluster?
 - Query Editor on Redshift
 - How to Load Data from S3 to Redshift?
 - What is Auto Scaling?
 - Project: Auto Scaling (Part 1)
 - Project: Auto Scaling (Part 2)
 - Quiz: Auto Scaling
 - Load Balancing?
 - Project: Load Balancer (Part 1: Configure the Instance)
 - Project: Load Balancer (Part 2: Configure the Load Balancer)
 - Project: Load Balancer (Part 3: Web Application Firewall)
 - Quiz: Load Balancing
 - Learning Path FREE PREVIEW
 - Amazon CloudWatch
 - How to create CloudWatch Dashboards?
 - Setup CloudWatch Alarms
 - Quiz: Cloudwatch
 - Amazon CloudTrail
 - How to use Amazon CloudTrail?
 - How to create custom Trail?
 - Quiz: Cloudtrail
 - AWS Trusted Advisor
 - How to use Trusted Advisor?
 - What is Serverless Computing?
 - How AWS Lambda Works?
 - Creating APIs using Lambda Functions
 - API with Parameters
 - Best Practices with AWS Lambda
 - Quiz: AWS Lambda
 - AWS Pricing Concepts
 - Billing Dashboard
 - AWS Budgets
 - How to Create an AWS Budget?
 - AWS Cost Explorer
 - Challenges Before Migration
 - AWS Cloud Adoption Framework
 - Cloud Migration Strategies
 - Quiz: Migration Strategies
 - AWS Snow Family
 - Quiz: Snow Family
 - AWS - Assignment
 
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Week 20 - Deep Learning
- What is Deep Learning? FREE PREVIEW
 - Difference b/w Deep Learning and Machine Learning FREE PREVIEW
 - Quiz: Difference between Machine Learning and Deep Learning
 - Why Deep Learning is so popular? FREE PREVIEW
 - Quiz: Why Deep learning is so popular?
 - Hardware for Computations in Deep Learning FREE PREVIEW
 - Setting up your system
 - Introduction to Google Colab FREE PREVIEW
 - Understanding Google Colab Interface FREE PREVIEW
 - Pre-requisites for Deep Learning
 - Structure of course FREE PREVIEW
 - Instructor introduction FREE PREVIEW
 - Course Handouts
 - Perceptron FREE PREVIEW
 - Quiz - Perceptron
 - Weights in Perceptron FREE PREVIEW
 - Quiz - Weights in Perceptron
 - Multi Layer Perceptron FREE PREVIEW
 - Quiz - Multi Layer Perceptron
 - Visualizing the neural network FREE PREVIEW
 - Understanding Decision Boundary
 - Forward and Backward Prop Intuition
 - Quiz - Visualizing the neural network
 - Quiz - Forward and Backward Prop Intuition
 - Gradient Descent Algorithm
 - Quiz: Understanding the decision boundary
 - Quiz - Gradient Descent Algorithm
 - Understanding Forward Propagation Mathematically
 - Quiz - Understanding Forward Propagation Mathematically
 - Understanding Backward Propagation Mathematically
 - Backward Propagation: Matrix Form
 - Quiz - Understanding Backward Propagation Mathematically
 - Why Numpy?
 - Quiz: Why Numpy?
 - Neural Network From scratch Using Numpy
 - Quiz: Implementation of Neural Network
 - Forward Propagation (using Numpy)
 - Backward Propagation (using Numpy)
 - Training network (using Numpy)
 - Why do we need activation functions?
 - Linear Activation Function
 - Quiz - Why do need activation functions
 - Quiz - Linear Activation Function
 - Sigmoid and tanh
 - Quiz - Sigmoid and tanh
 - Quiz - ReLU and LeakyReLU
 - ReLU and Leaky ReLU
 - Quiz - Softmax
 - Tips to selecting right Activation Function
 - Softmax
 - Variants of Gradient Descent
 - Quiz: Tips to selecting right activation function
 - Quiz - Variants of Gradient Descent
 - Problems with Gradient Descent
 - Quiz - Problems with Gradient Descent
 - RMSProp
 - Quiz - RMSProp
 - Adam
 - Quiz: Adam
 - Assignment: Big Mart Sales Prediction
 - Introduction to loss function
 - Introduction to loss function
 - Binary and Categorical Cross entropy / log loss
 - Quiz - Binary and Categorical cross entropy / log loss
 - Overview of Deep Learning Frameworks
 - Quiz - Overview of deep learning frameworks
 - Understanding important Keras modules
 - Quiz: Understanding important Keras Modules
 - Understanding the problem statement: Loan Prediction
 - Data Preprocessing: Loan Prediction
 - Quiz - Data Preprocessing: Loan Prediction
 - Steps to solve Loan Prediction Challenge
 - Loading loan prediction dataset
 - Quiz: Understanding the problem statement : loan prediction
 - Defining the Model Architecture for loan prediction problem
 - Quiz: Defining the model architecture for loan prediction problem
 - Training and Evaluating model on Loan Prediction Challenge
 - Quiz - Training and Evaluating model on Loan Prediction Challenge
 
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Week 21 - Deep Learning
- Functional API for Deep Learning
 - Quiz - Functional API for Deep Learning
 - Solving Loan Prediction Using Functional API in Keras
 - Building a custom Model Using Functional API in keras
 - Quiz - Building a Model Using Functional API
 - How are images stored?
 - Quiz - How are images stored
 - Different Image Formats
 - Quiz - Different Image formats
 - Reading and stacking Images
 - Quiz: Reading and stacking images
 - Converting images into different formats
 - Quiz - Converting image into different formats
 - Extracting edges from images
 - Quiz - Extracting edges from images
 - Implementation: Extracting edges from images
 - Quiz - Extracting edges implementation
 - Project: Image Classification "Emergency Vs Non-Emergency Vehicle"
 - Notebook: Neural Network in Keras and Hyperparameter Tuning
 - Neural Network in Keras
 - Quiz: Neural network in keras
 - Hyperparameter Tuning for MLP in Keras
 - Quiz: Hyperparameter tuning for MLP in keras
 - Early stopping
 - Early stopping: Implementation
 - Quiz - Early stopping: Implementation
 - Dropout
 - Dropout: Implementation
 - Quiz - Dropout: Implementation
 - Vanishing and Exploding gradients
 - Quiz: Vanishing and exploding gradients
 - Vanishing and Exploding gradients: Implementation
 - Quiz - Vanishing and exploding gradient: Implementation
 - Weights Initialization Techniques
 - Quiz: Weight Initialization techniques
 - Implementing different weight initializing techniques
 - BatchNorm
 - Quiz: Batch Normalization
 - BatchNorm: Implementation
 - Advantages of Batch Normalization
 - Quiz - Advantages of Batch Normalization
 - Image Augmentation Techniques
 - Image Augmentation Techniques: Implementation
 - Quiz: Image Augmentation: Implementation
 - Image Augmentation on Emergency-non emergency dataset
 - Image Generator and Fit Generator
 - Quiz: Image Generator and Fit generator
 - Model Checkpointing
 - Quiz: Model Checkpointing
 - Implementing model checkpointing
 - Assignment: Gender Classification
 
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Week 22 - Overview of Data Engineering & Mastering Apache Spark Using Python
- Introduction to the Course
 - What is Data Engineering?
 - Demand for Data Engineers
 - Course Handouts
 - Case Study - Year 2014
 - Case Study - Year 2016
 - Case Study - Year 2017
 - Case Study - Year 2021
 - Skillset Required apart from Technical Skills
 - Course Overview
 - Pre-requisites
 - Instructor Introduction
 - Course Handouts
 - What is Big Data?
 - Challenges with Big Data
 - Applications of Big Data
 - Quiz: Big Data
 - Distributed Systems
 - Quiz: Distributed Systems
 - Introduction to Apache Hadoop
 - Components of Apache Hadoop
 - Hadoop Ecosystem
 - Quiz: Introduction to Hadoop
 - What is Spark?
 - Spark Ecosystem
 - Quiz: Introduction to Apache Spark
 - Spark Architecture
 - Quiz: Spark Architechture
 - Spark Cluster Managers
 - Running Spark Applications on YARN
 - Spark Context and Spark Sesssion
 - Quiz: Spark Cluster Managers
 - Itversity Credentials
 - Introduction to Itversity
 - Uploading data to Itversity
 - HDFS common commands
 - What Are RDDs?
 - How to create RDDs?
 - Implementation: How to create RDDs?
 - RDD Operations
 - Implementation: RDD Operations(Part 1)
 - Implementation: RDD Operations(Part 2)
 - Quiz: RDD
 - Pair RDDs
 - Pair RDD Operations
 - Implementation: Pair RDD Operations
 - Implementation: GroupByKey Vs ReduceByKey
 - Quiz: Pair RDD
 - Caching and Persistence in Spark
 - Implementation: Persistence
 - Storage Levels in Spark
 - Implementation: Storage Levels
 - Quiz: Caching & Persistence
 - Assignment: RDD Operations
 
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Week 23 - Overview of Data Engineering & Mastering Apache Spark Using Python
- What are Spark DataFrames?
 - Implementation: Creating Spark DataFrames
 - Implementation: Basic Operations on DataFrames
 - Implementation: Creating Columns in DataFrames
 - Implementation: Manipulating Records in DataFrames
 - RDDs Vs DataFrames - When to use?
 - Quiz: DataFrames in Spark
 - Assignment: Spark DataFrames
 - Jobs, Stages and Tasks
 - Implementation: Jobs, Stages and Tasks
 - Lineage
 - Implementation: Lineage
 - DAG
 - Implementation: DAG
 - Quiz: Spark Execution
 - Shared Variables
 - Implementation: Shared Variables
 - Shuffling
 - Partitioning
 - Coalesce vs Repartition
 - Implementation: Coalesce vs Repartition
 - Quiz: Advance Programming in Spark
 - What is Spark SQL?
 - Catalyst Optimizer
 - Spark SQL Queries
 - Implementation: Spark SQL Queries
 - Why do we need Spark SQL?
 - Quiz: Spark SQL
 - Assignment: Spark SQL
 - Scope of ML in this Course
 - Introduction to Machine Learning
 - Types of Machine Learning Problems
 - Machine Learning in Spark
 - Life Cycle of a ML Project
 - Quiz: Machine Learning in Spark
 - Understanding the Problem Statement
 - Implementation: Introduction to the Data
 - Implementation: Univariate Analysis
 - Implementation: Bivariate Analysis
 - Quiz: Analysis using Spark
 - Encoding Categorical Variables
 - Implementation: Preprocessing Data
 - Quiz: Preprocessing data using spark ML
 - Vector Assembler
 - Implementation: Model Building
 - Quiz: Model Building
 - Model Improvement
 - Implementation: Fine Tuning ML Models
 - Quiz: Fine Tune ML Models
 - Understanding ML Pipelines in Spark
 - Implementation: Sample Pipelines in Spark
 - Implementation: ML Pipeline for Click Prediction
 - Quiz: ML Pipelines
 - Assignment: Spark ML
 
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Week 24 - Model Deployment
- Introduction to Model Deployment
 - Overview of the Course
 - Projects covered in the Course
 - Model Deployment tools covered in the Course
 - Instructors of the Course
 - Course Handouts
 - Advance Python, Basics of Machine Learning and Deep Learning
 - Introduction to git
 - Introduction to Linux Commands
 - Setting up your machine
 - Outline of the Module
 - Quiz: Outline of the Module
 - Understanding the problem statement
 - Steps to build the Loan Eligibility Application
 - Quiz: Steps to build the Loan Eligibility Application
 - Frontend of the Loan Eligibility App
 - Quiz: Frontend of the Loan Eligibility application
 - Deploying rule based model using streamlit
 - Exercise: Deploying rule based model using Streamlit
 - Deploying machine learning model using streamlit
 - Exercise: Deploying machine learning model using Streamlit
 - Summarizing the module
 - Build a Big Mart Sales Prediction Application
 - Introduction to Amazon Web Services (AWS)
 - Quiz: Introduction to Amazon Web Services
 - Spinning up an AWS server
 - Quiz: Spinning up an AWS server
 - Deploying ML model using Streamlit and AWS
 - Quiz: Deploying ML model using Streamlit and AWS:-
 - Overview of the module
 - Building an Image Classification model
 - Exercise: Building an Image Classification model
 - Deploying Image Classification model using Streamlit and AWS (Part I)
 - Deploying Image Classification model using Streamlit and AWS (Part II)
 - Quiz: Deploying Image Classification model using Streamlit and AWS
 - Understanding Text Generation Project
 - Create front-end of the Project
 - Create front-end of the Project - Implementation
 - Quiz: Create front-end of the Project
 - Building a Text Generation model
 - Exercise: Building a Text Generation model
 - Deploying Text Generation model using Streamlit
 - Quiz: Deploying Text Generation model using Streamlit
 - Deploying Text Generation model using Streamlit on AWS
 - Setting up an accessible website
 - Outline of the module
 - Introduction to Amazon Sagemaker
 - Quiz: Introduction to Amazon SageMaker
 - Understanding the problem statement: Cardiac Arrest Predictor
 - Quiz: Understanding the Problem Statement: Cardiac Arrest Predictor
 - Setting up Amazon SageMaker
 - Building a Machine Learning model on Amazon Sagemaker
 - Exercise: Building a machine learning model on sagemaker
 - Deploying the Machine Learning model using Amazon Sagemaker
 - Using SageMaker Endpoint to generate Inferences
 - Build and Deploy Big Mart Sales Prediction model on Amazon SageMaker
 - Introduction to Flask for Model Deployment
 - Deep dive into APIs
 - Quiz: Deep dive into APIs
 - Understanding the Problem Statement
 - Building an ML model for Cardiac Arrest Prediction
 - Exercise: Building an ML model for Cardiac Arrest Prediction
 - Deploying ML model using Flask
 - Understand the Project - Transcript Generation
 - Building a DL model for Transcript Generation
 - Deploying Transcript Generation model using Flask
 - Exercise: Deploying Transcript Generation model using Flask
 - Summary and Where to go from here
 
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Resources
- Articles Link