What is Data Analytics, DS, AI/ML - bepec.in

Course Content

Data Science Course Syllabus

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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

Advanced Data Structures and Algorithms

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Introduction to DSA

Non-Primitive Data Structures

Non-Linear Data Structures

What is an Algorithm

Theory & Code Implementation of Linked List

Stacks & Queues Assignment

Coding Stack Data Structure

Coding Queue Data Structure

Tree Data Structures

Types of Tree Data Structure

Bubble Sort Theory

Bubble Sort Code Implementation

Selection Sort Theory

Selection Sort Code Implementation

Insertion Sort Theory

Insertion Sort Code Implementation

Merge Sort Theory

Merge Sort Code Implementation

Quick, Merge Sort Performance

Quick Sort Theory

Linear Search & Bisection Search

Applied Statistics

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What is Data? Various Types of Data

Levels of Measurement

Categorical Variables & Visualisation Techniques

Continuous Variables and Visualisations

Measures of Central Tendency

Measuring Skewness

Measures of Dispersion

Covariance & Correlation Coefficient

Box & Whisker Plot

Outlier Identification

Treating Outliers

Sampling Techniques

Statistical Analysis Consideration

Types of Analytics

Sample vs Population

Introduction to Inferential Statistics

Law of Large Numbers

Central Limit Theorem

Probability Distributions

Conditional Probability

Continuous Probability Distribution & Discrete Probability Distribution

PMF, CDF, PDF, PPF in Probability

Binomial Distribution

Poisson Distribution

Normal Distribution

Exponential Distribution

Laplace Distribution

Log-Normal Distribution

Confidence Interval Calculations

Z-Table for Confidence Interval

T-Table for Confidence Interval

Hypothesis Testing

Null & Alternate Hypothesis

Type-1 Error & Type-2 Error

2-Sample T Test

p-Value Calculations

Chi-Square Test

Project Demonstration using all the Statistical Techniques

Mastering Excel

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Introduction to Excel

Basics of Excel Commands

Conditional Formatting in Excel

Different Calculations in Excel

Different Charts in Excel

Pivot Tables in Excel

Slicers in Excel

Filters in Excel

VlookUp, HLookup

Conditional Statements in Excel

SumIF & Count IF

Data Analysis Tool Kit

Forecasting in Excel

Correlation in Excel

Regression in Excel

What-If Analysis

Scenario Manager

End-to-End Dashboard using Excel

Power Query in Excel

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

Real-Time Project Demonstration on 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

Real-Time Project Demonstration on Data Analysis Using Excel

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Real-Time Project Demonstration on Data Analysis using Excel

Real-Time Project Demonstration on 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

Real-Time Project Demonstration on 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

Advanced MySQL

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Data Integrity & Referential Integrity

Data Normalisation

First & Second Normal Form

Functional Dependency, Transitive Dependency & 3rd Normal Form

Boyce-Codd Normal Form

Denormalization

Temporary Table, Common Table Expression, Recursive CTE

When to use Temporary Table, CTE & Recursive CTE

Subquery in MySQL

Stored Functions

Stored Procedures

Triggers in MySQL

Create Events in MySQL

Different Functions in MySQL

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

Feature Engineering Techniques

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Feature Scaling Techniques

Standardisation

Label Encoding Technique

One-Hot Encoding Technique

Dummies Technique

Ordinal Encoding Technique

Imputation Technique

Feature Selection Techniques

Filter Method: Feature Importance

Filter Method: Fishers Score Technique

Filter Method: Chi-Square Technique

Filter Method: Variance Threshold

Filter Method: Correlation Coefficient

Filter Method: Mutual Information

Wrapper Method: Forward Selection Technique

Wrapper Method: Backward Selection Technique

Wrapper Method: Recursive Feature Elimination Technique

Wrapper Method: Exhaustive Feature Selection Technique

Wrapper Method: Sequential Feature Selection Technique

Embedded Methods: Regularisation

Embedded Method: Elastic Net Regression

Embedded Method: Decision Tree

Outlier Treatment

Over Sampling Technique

Under Sampling Techniques

Supervised Learning[70% Interview Questions]

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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

Introduction to PCA

Math behind PCA

AutoML Using Pycaret

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

PySpark: BigData Processing

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Introduction to Spark

Various divisions in Spark

Python with Spark

Pyspark for MLLib

Spark DataFrames

Spark Operations

Grouping, Aggregating and Joining with Spark

Introduction to Machine Learning with PySpark

Machine Learning Pipeline with Spark

Frequent Pattern Mining and Statistics

Feature Transformation with Spark

Data Cleaning & Pre-Processing with Spark

NLP with Pyspark

Spark Structured Streaming

Streaming ML Solutions

MongoDB Mastering

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Introduction to Mongo DB

Installation of MongoDB

Basics Operations of MongoDB

Create Operations in MongoDB

Update Operations in MongoDB

Read Operations in MongoDB

Delete Operations in MongoDB

Query & Projection Operations

Python with MongoDB

Spark with MongoDB

Real-Time Projects to Work as Part of Job Simulation

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Data Analytics Real-Time Project-1

Data Analytics Real-Time Project-2

Data Analytics Real-Time Project-3

Data Analytics Real-Time Project-4

Data Science Real-Time Project-1

Data Science Real-Time Project-2

Data Science Real-Time Project-3

Data Science Real-Time Project-4

Real-Time NLP Project-1

Real-Time NLP Project-2

Real-Time NLP Project-3

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

Azure Machine Learning Engineering

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Introduction to Azure Environment

Training & Tuning ML Models using Azure

Working with Data in Azure

Training ML Models in Azure ML

Tuning ML Models in Azure

Azure Automated ML

Deploying & Explaining ML Models

Deploying ML Model for Real-Time Inferencing

Deploying ML Models for Batch Scoring

AWS Sagemaker Studio

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Setting up AWS Sagemaker & Deploying Simple ML Model

AIOps with AWS Sagemaker Studio

Hadoop

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Introduction to Hadoop

Understanding HDFS

Using HDFS Command Line

Using HDFS Web Interface

Hadoop MapReduce

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Introduction to MapReduce

MapReduce Platform

Parallel MapReduce

MapReduce Examples

MapReduce YARN Examples

HIVE Database

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Introduction to HIVE

Working on HIVE “SQL” commands

Various Examples on Hive

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

Computer Vision Mastering using Tensorflow

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Introduction to Object Detection vs Object Classification

Introduction to CNN

Convolution Matrix

Max Pooling Layer

Point-Wise & Element-Wise Convolution

Batch Normalisation

Strides & Padding

Convolution Filters

End-to-End Computer Vision

Transfer Learning with OpenCV & YOLO

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Introduction to Transfer Learning

Headless & With Head Transfer Learning

Object Detection using YOLO

Object Detection using Open CV

Transfer Learning with Tensorflow Hub

Introduction to Generative AI

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What is Generative AI?

Generative Models & Discriminative Models

Types of Generative Models

Applications of Generative AI

How to Automate Work with Generative AI?

What is Responsible AI?

What is Representation Learning?

Generative AI End-to-End Project Lifecycle

GenAI, prompt Engineering using LangChains

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What is Generative AI? Use cases in text, image, code, and conversation

Foundation Models: GPT, Claude, PaLM, Gemini, Mistral, LLaMA

Introduction to Lang Chains

Using LLMs using Lang Chains

What is Prompt Engineering

Prompt Engineering Principles

Zero-shot, Few-shot, Chain-of-Thought (CoT)

Best Way to Improve LLMs Accuracy

Doing Prompt Engineering using Lang Chains

PromptTemplate best practices with LangChain

Using ChatPromptTemplate, SystemMessagePrompt, HumanMessagePrompt

Prompt evaluation: temperature, top_p, stop, max_tokens

Retrieval-Augmented Generation (RAG) with LangChain

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Why RAG? Token limits, context injection

Vector Embeddings: OpenAI, HuggingFace, Cohere

Vector DBs: FAISS, Pinecone, Chroma, Weaviate, Milvus

LangChain’s RetrievalQA Chain

Chunking strategies and TextSplitter

Hybrid search: Dense + Metadata filtering

SequentialChain vs SimpleSequentialChain

RunnablePassthrough, RunnableLambda (LCEL)

Creating Tool abstractions with @tool decorator

Integrating APIs (e.g., SerpAPI, Weather, Calculator)

Output parsers: StrOutputParser, StructuredOutputParser

Agentic AI – Build Autonomous Agents with LangChain

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What is Agentic AI vs traditional agents

Types of agents in LangChain: ReAct, ConversationalReAct, Plan-and-Execute, OpenAIFunctionsAgent

Agent memory (ConversationBufferMemory, SummaryMemory)

Task Decomposition and Planning

Use Cases: Code generation, Auto-documentation, Research Assistants

Model Context Protocol (MCP) and Multi-Agent Architectures

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What is Model Context Protocol (MCP)

Context-aware decision making

Prompt-as-function vs Function-as-prompt

Designing structured workflows (LangGraph overview)

Communication between agents

Build an MCP-based RAG agent

Implement agent-to-agent communication where one retrieves, another summarizes, and a third decides actions

Fine-Tuning and Pretraining Language Models

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Difference between Pretraining, Fine-Tuning, Instruction Tuning

Fine-Tuning Open Source Models (LLaMA, Mistral, Falcon)

PEFT Techniques: LoRA (Low-Rank Adaptation) Adapters Prefix-Tuning

Tools: HuggingFace Transformers, PEFT, DeepSpeed, bitsandbytes

Full Stack Application + Deployment(LLMOps)

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Combining RAG, Agentic AI, and Fine-tuned models

Deploying LangChain applications on: Streamlit, Solara, FastAPI, Gradio

CI/CD Pipelines for LLMOps

Monitoring and Cost Management (OpenAI + LangSmith + Tracing)

Build an End-to-End Custom Knowledge Assistant: Ingest PDFs/Docs Chunk and Embed to Vector DB Query using Conversational Agent (RAG + Tools + Planner) Deploy using Solara

Advanced Deep Learning

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Building Blocks of Artificial Neural Networks

What are Optimisers and Types of Optimisers

Math Behind Feed Forward Neural Network

Math Behind BackPropagation

Why Activation Functions & Importance

Introduction to Tensorflow

FFNN-Regression Script using Tensorflow

FFNN – Classification Script Using Tensorflow

Feed Forward Neural Network Coding

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Back Propagation

Feed Forward Script Explanation

Introduction to Tensorflow & Feed Forward Neural Network

Open AI – Mastering

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Introduction to Open AI

Creating Open AI Keys

Implementing Vision Based Generative Models using Open AI

Implementing Text Based Generative Models using Open AI

Speech to Text Implementation with Open AI

Fine-Tuning LLMs with Custom Data

Mastering LangChains

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Introduction to LangChains

LangChains Architecture

Components of Langchains

Fine-Tuning Prompts with LangChains

ChatBot with LangChains

Q & A with LangChain

Text Summarisation with LangChain

Different Prompt Template with Langchain

Document and File Analysis with LangChains

Hugging Face Models with LangChains

Falcon Fine-Tuning

Mistral Fine-Tuning on Custom Data

LLaMA2 with LangChains

PalM2 with LangChains

LangChain with Streamlit & Flask Deployment

Prompt Engineering with LangChains and Open AI

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What is Prompt Engineering?

Types of Prompt Engineering

Zero, Single & Few Shot Prompt Engineering

Implementing Prompt Templates

Reducing Hallucination Rate with Prompting

Providing Context with Prompts

Emotional Based Prompts

End-to-End Project Prompt Engineering Implementation using LangChains & Open AI

Topic Modelling

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Introduction to NLP & NLP Applications

NLP Pre-Processing Techniques

NLP Feature Extraction

Project Demonstration: NLP Classification Project

What is N-Gram & Why N-Gram Technique

Coding N-Gram Technique

What is Word2Vec?

Word2Vec Algorithms like CBOW & Skip-Gram

Case Study: Coding Word2Vec Model

What is latent dirichlet allocation? Why LDA

What is Topic Modelling?

Case Study: Coding Topic Modelling

Convolution Neural Network – Math & coding

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Introduction to CNN & Why CNN Algorithm

What is Object Detection & Object Classification

Intuitive Understanding Behind CNN

Math Behind CNN

CNN Coding using Tensorflow

CNN Coding using Keras

Types of CNN Networks

What is Transfer Learning

Tensorflow Hub & Various Pre-Trained Models

Using Pre-Trained Models for Object Classification

Deploying Image Classification Model in AWS

Project Demonstration: Image Classification Project

Mastering NLU

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What is NLU & Why NLU

What is POS Tagging

Case Study: Coding POS Tagging

What is Dependency Parsing?

What is Constituency Parsing?

Case Study: Coding Dependency & Constituency Parsing

What is NER? & Usage of NER

Case Study: Coding NER

What is Coreference Resolution?

History of NLU Models

Project Demonstration: NLU Classification Model using LSTM

What is Encoder & Decoder Model

Math Behind Encoder-Decoder Models

What is Attention Based Models

Math behind Attention Based Models

Case Study: Coding Attention Based Models

MLOps for Transformer Models

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Introduction to MLOps

Model Sharing on HuggingFace

BERT Model Deployment using FastAPI

Modern Language Models like GPT-3 & ChatGPT

Data Science Real-Time Projects End-to-End & Portfolio Building

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End-to-End Data Modelling using Snow Flake

Data Ingestion, Data Transformation, Data Storage and Data Analysis – DataOps Pipeline Demonstration

Real-Time Data Integration and Analytics Platform

End-to-End Data Science Project with Amazon S3, Snow Flake, Spark & Snow Park

End-to-End Data Science Project Using Spark & Microsoft Fabric

AGILE CRISP: End-to-End Data Science Project Pipeline

Agile DataOps for Real-Time Credit Risk Scoring and Analysis

MLOps Pipeline: End-to-End Data Science Lifecycle using MLOps

Streaming Analytics: End-to-End Data Science Project

Generative AI End-to-End Projects

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Document Summariser Project using LangChains, Open AI, Streamline & AWS Deployment

Medical Q & A Generative Model with LangChain, Open AI, Streamline & AWS Deployment

Product Recommendation Generative Model using LLaMA2, Streamlit, LangChain & AWS

ChatBot with LangChain, Streamlit, Open AI & AWS Deployment

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 Questions: Frequently Asked Statistics

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Introduction to Statistics

Properties of Data

Sample vs Population

Types of Sampling Techniques

Exploratory Data Analysis

Analysing Data with Applied EDA

Measures of Dispersion

Skewness & Normality

Correlation & Scatterplot

Barplot & Lineplot

Mindmaps for Interview Revision

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Data Science Interview Revision Mindmap

Statistics Mindmap

Python Learning Mindmap

SQL Interview Mindmap

Machine Learning Accuracy Improving Techniques Mindmap

Machine Learning Math Mindmap

Real-Time Project Procedure Mindmap

ML Framework Mindmap

Power BI Interview Mindmap

NLP Interview Mindmap

Deep Learning Interview Mindmap

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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Handwritten Notes

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Python Handwritten Notes

SQL Handwritten Notes

Live Classes

Data Science Course 3.0 with Gen AI Job-Oriented Program

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