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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8
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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9
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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10
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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11
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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12
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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13
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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14
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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15
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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16
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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17
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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18
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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19
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