Course Content

Introduction to Data Analytics, Data Science, AI, ML Roadmap

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What is Data Analytics, DS, AI/ML

Interview Preparation Roadmap on Data Analytics, Data Science, AI & ML

Induction Classes

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What is Data, Importance of Data

What are Mathematical Equations? Why ME?

Fourier Transformation & Fourier Series

What is Probability and Why Probability

What is Geometry, What is Linear Algebra, Eigen Values and Eigen Vectors

What is Calculus

Mastering Python[Zero to Hero]

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Introduction to Python

Why Python, Value, Variable, Function, Library[Roadmap on Python]

IDE in Python, Different Data Types

List, Tuple, Set & Dictionary Overview

Different List Methods

Different Tuple Methods

Set & Frozenset

Dictionary & String Manipulations

Overview on Loops, If Statements, UDFs, Escape Sequences, Lambda

Types of Operators, Conditional Statements

While Loop, List Comprehension, Break, Continue, Arguments

Functions, Escape Sequences, Lambda Functions

Introduction to OOPS

Instance Variable, Class Variable, Class Method

Association vs Composition & Aggregation

Encapsulation, Inheritance

Polymorphism, Method OverLoading, Method Overriding

Introduction to Pandas

Data Analysis using Pandas

Introduction to Numpy

Different Numpy Commands

Introduction to Data Visualisation

Data Visualisation using Matplotlib

Data Visualization using Seaborn

Data Visualization using Plotly

Why Data Cleaning?

Data Cleaning with Sklearn & Pandas

Regular Expression Basics

Statistics with Real-Time Project Demonstration on EDA

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Basics of Statistics

Central Limit Theorem, Normal Distribution, Skewness

Real-Time Project Demonstration on EDA with Real-World Project

End-to-End Statistics using Excel

Probability Distributions, Hypothesis Testing

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Probability Distribution, Random Variable, Binomial, Poisson, Exponential

Normal Distribution

Real-Time Project Demonstration on Probability

Hypothesis Testing Part-1

Hypothesis Testing Part-2

How to Calculate P-Value? Coding Hypothesis Testing

How to solve PDF, CDF, PMF?

Chebyshevs, Log, Power Law, Q-Q, CLT

End-to-End Data Analysis Using Excel

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End-to-End Data Analysis using Excel

End-to-End Data Analysis using Power BI & MySQL

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End-to-End Data Analysis using Power BI

Data Analysis using MySQL

Data Analysis using MySQL & DAX Calculations Power BI

How to Prepare for Data Analytics Interviews

End-to-End Data Analysis using Tableau

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End-to-End Data Analysis using Tableau

Mastering MySQL

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Introduction to MySQL

Creating Database in MySql

Deep Dive into MySQL

SELECT, UPDATE, DELETE Operations

Clauses in MySql Part-1

Clauses in MySql Part-2

Clauses in MySQL Part-3

MySQL Data Handling Part-1

MySQL Data Handling Part-2

Mastering Tableau[Zero to Hero]

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Introduction to Tableau

Basics of Tableau

Different Types of Charts

Table Calculations & Parameters

Waterfall, Pareto Chart, Filters in Tableau

LOD Expression & Pareto Chart

MySQL Connection with Tableau

End-to-End Project using Tableau

Connect Tableau Desktop with Server

Tableau Server, Scheduling & Alerts

Tableau Interview Preparation

Mastering Power BI[Zero to Hero]

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Introduction to Power Bi

Creating a Bar Plot

Creating Pie Chart

Creating Ribbon Chart

Creating Scatter Plot

Creating WaterFall Charts

Creating Funnel Chart

Creating Line Plot & Area Plot

Creating Matrix & Conditional Formatting

Creating Decomposition Tree

Creating KPI Card

Creating Gauge Card

Creating Slicers

Creating Animated Bar Plot

Creating Sunburst Chart

Different Filers in Power BI

Include & Exclude Operations in Power BI

Introduction to Power Query

Groupby & Replace in Power Query

Merge and Append Operations

Prefix, Suffix, Length

Pivot in Power Query

Introduction to DAX Expressions

Creating DAX Measures

Creating DAX Columns

More DAX Expressions

Publishing Power BI Visualizations

Unsupervised Learning with Real-Time Projects

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Supervised vs Unsupervised Learning

Fundamentals of Machine Learning Part-1

Fundamentals of Machine Learning Part-2

Insights from Train & Test Accuracy

Associate Rules Part-1

Associate Rules Part-2

Problem Identification & Approach Designing

Associate Rules Scripting

Why to do Dimensionality Reduction? Project Implementation using PCA & T-SNE

Supervised Learning Algorithms

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How to Prepare Machine Learning Math for Interviews

Why to use Linear Regression?

What is Linear Regression

Case Study on Linear Regression

Math Behind Linear Regression Part-1

Math Behind Linear Regression Part-2

Math behind OLS Technique

Assumptions of Linear Regression

Evaluation Metrics for Regression Model

Accuracy Improving Techniques

Coding Linear Regression Model

Regularisation Techniques

Why Logistic Regression

Math Behind Logistic Regression

Evaluation Metrics Behind Classification Algorithms

ROC & AUC Curve

Coding Logistic Regression Model

Introduction to Decision Tree

Intuition Behind Decision Tree

Math Behind Decision Tree

Math Behind Decision Tree using GINI

Drawbacks of Decision Tree

Random Forest and Gradient Boosting

Coding Decision Tree, Random Forest, GB

SMOTE Technique to Handle Imbalanced Dataset

Filter Method, Wrapper Method, Embedded Method – Feature Selection Techniques

Coding Feature Selection Techniques

Math Behind KNN

Math Behind SVM

Mastering NLP, NLU, NLG

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Introduction to NLP, NLP Applications

NLP Pre-Processing Techniques

NLP Feature Extraction Techniques

NLP Practical Example

NLU, Word2Vec, RNN, NER

ML Deployment & MLOps

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End-to-End Deployment Using MLOps & Streamlit

Setup Virtual Environment

Docker Installation

How to Activate Virtual Environment

Regression Model using Pycaret

Regression Model using Pycaret Part-2

Interpretability of Model using SHAP

Application Development using Gradio

Creating API using FASTAPI

Creating Docker Image

Model Versioning using Pycaret & MLFlow

End-to-End ML Proof of Concept

Advanced Time Series with Real-Time Projects

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Introduction to Time Series Modelling

Time Series Modelling Part-2

Characteristics of Time Series Modelling

Time Series Modelling Techniques

Simple Time Series Project End-to-End

End-to-End Project on Time Series Modelling

AWS Sagemaker Studio

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Setting up AWS Sagemaker & Deploying Simple ML Model

AIOps with AWS Sagemaker Studio

Deep Learning, Tensorflow & Keras

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Introduction to Neural Networks

What are Optimisation Techniques

Math Behind Feed Forward Neural Networks

Back Propagation Techniques

Why Activation Functions

Regression using Tensorflow

Feed Forward Classification using Keras

End-to-End Computer Vision

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End-to-End Computer Vision

R Programming

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Installation of R Studio

Basics of R Studio

Data Visualisation with R Studio

Data Modelling with R Studio

Data Joining with R Studio

Data Visualisation with GGPlot2

Data Preparation with R Studio

Data Cleaning with Regexp

Data Visualisation with Plotly

Interview Preparation

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How to build Linkedin Profile

Resume Preparation for Data Science

Do’s and Don’t while Marketing our Resume

Do’s and Don’ts in LinkedIn/Job Portals

3 Elements to Crack Any Interview

Course Files

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Private: Full Stack Data Science – #BuildExperience Program

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