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Data Science

Data Science

What you will learn?


Understanding Full Stack Development.

Roles and Responsibilities of a Full Stack Developer.

Overview of Frontend and Backend Technologies.

HTML, CSS, and JavaScript Basics

HTML5 Markup and Document Structure.

CSS3 Styling and Layouts.

Introduction to JavaScript, DOM Manipulation.

Responsive Design and Frameworks

Responsive Web Design Principles.

Bootstrap Framework.

CSS Preprocessors (e.g., SASS).

JavaScript Frameworks

Introduction to JavaScript Frameworks (React, Angular, or Vue)

Building Single Page Applications (SPAs)

Server-Side Programming with Node.js

Introduction to Node.js.

Building RESTful APIs with Express.

Middleware and Routing.

Database Management

Relational Databases (e.g., MySQL, PostgreSQL).

NoSQL Databases (e.g., MongoDB).

Database Design and Querying.

Server Deployment and Management

Deploying Node.js Applications.

Setting up Cloud Hosting (e.g., AWS, Heroku).

Application Monitoring and Maintenance.

Git and GitHub

Introduction to Version Control.

Git Basics: Commits, Branches, Merging.

Collaborative Development with GitHub.

MEAN or MERN Stack

Overview of MEAN (MongoDB, Express.js, Angular, Node.js) or MERN (MongoDB, Express.js, React, Node.js) stack.

Building a Full-Stack Application.

Testing Basics

Unit Testing and Integration Testing.

Test-Driven Development (TDD).

Code Quality and Code Review Best Practices.

DevOps Principles

Continuous Integration (CI) and Continuous Deployment (CD).

Automation with Jenkins or GitLab CI.

Containerization with Docker.

Microservices Architecture

Introduction to Microservices.

Building and Deploying Microservices.

API Gateway and Service Mesh.

Security in Full Stack Development

Web Application Security.

Secure Coding Practices.

Handling Authentication and Authorization.

What you will learn?

Understanding the Digital Landscape

Introduction to digital marketing concepts.

Overview of the digital marketing ecosystem.

Key channels, platforms, and technologies.

Evolution of Marketing in the Digital Age

Historical context of marketing.

Shift from traditional to digital marketing.

Importance of digital marketing in the modern business landscape.

Basics of Website Structure and Design

Understanding website architecture.

Importance of user-friendly design

User Experience (UX) and User Interface (UI) Design

Principles of UX/UI design.

Creating a positive user experience.

Mobile responsiveness and its significance.

Fundamentals of SEO

Introduction to search engine optimization.

Importance of organic traffic.

Keyword Research and Analysis

Conducting keyword research.

Analyzing keyword competitiveness.

On-Page and Off-Page Optimization basics.

Introduction to Social Media Platforms

Overview of major social media platforms.

Identifying target audiences on social media.

Social Media Strategy and Planning

Developing a social media strategy.

Content calendar creation.

Content Strategy and Planning

Understanding content marketing.

Creating a content strategy.

Blogging and Article Writing

Writing engaging blog posts.

Content distribution strategies.

Building and Managing Email Lists

Strategies for growing email lists.

Importance of segmentation.

Email Campaign Strategy

Designing effective email campaigns.

Analyzing email marketing analytics.

Introduction to Paid Advertising

Basics of paid advertising.

Understanding PPC.

Google Ads and Bing Ads

Creating and optimizing Google and Bing ad campaigns.

Display advertising and remarketing.

Introduction to Analytics Tools

Overview of tools like Google Analytics.

Setting up analytics for a website.

Data Analysis and Reporting

Interpreting analytics data.

Creating reports for performance analysis.

Conversion tracking and optimization.

Identifying and Engaging Influencers

Strategies for finding relevant influencers.

Approaching and engaging with influencers.

Negotiating and Measuring Influencer Campaigns

Negotiating terms with influencers.

Measuring the success of influencer campaigns.

Building long-term relationships with influencers.

Developing a Digital Marketing Plan

Crafting a comprehensive digital marketing plan.

Setting goals and objectives.

Budgeting and Resource Allocation

Allocating budgets for various channels.

Resource planning for campaigns.

Continuous monitoring and adjusting the strategy.

Privacy Laws and Regulations

Overview of data protection laws.

Ensuring compliance in digital marketing.

Ethical Practices in Digital Marketing

Understanding and practicing ethical marketing.

Building trust with consumers.

Artificial Intelligence in Marketing

Role of AI in marketing.

Automation and personalization.

Voice Search and Smart Assistants, Augmented Reality (AR) and Virtual Reality (VR) in Marketing

Adapting to voice search trends.

Utilizing AR and VR in marketing strategies.

Applying all learned concepts to a real-world scenario.

Developing and implementing a comprehensive digital marketing campaign.

Presenting and analyzing the results.

What you will learn?

Understanding Excel Interface

Installation and Microsoft Terms and Conditions

Basic Excel Shortcuts

Data Visualisation in Excel

Conditional Formatting, VLOOKUP, HLOOKUP, Pivot Table

Dashboard Presentation in Excel

Mathematics for Data Science

Fundamentals of Calculus

Permutation and Combination

Basics of Probability

Fourier Series/Integration

Matrix Algebra

Introduction to Python Programming

Installation Of Anaconda Navigator

Data Types in Python

Operations in Python

Control Structures in Python


OOPs in Python (Optional)

Python for Data Science

Introduction to NumPy

Operations in NumPy

Indexing NumPy Arrays

Panda Series and DataFrames


Groupby Functions

Joining, Concatenating and merging DataFrames

Data Visualisation in Python

Data Visualisation Using Matplotlib

Data Visualisation Using Seaborn


Exploratory Data Analysis

Web Scraping

Data Wrangling

Data Preparation

Missing Value Imputation


Introduction to Database Design

Understanding ERD

Various Constraints in SQL

Star Schema

Database Creation and Modification in MySQL workbench

Queries in SQL

Combining Tables

SELECT Statement

Advanced Filtering

SQL Transactions, Variables and Procedures

Descriptive Statistics

Types of Data

Population VS Sample

Central Tendency

Measures of Dispersion


Inferential Statistics

Probability and Probability Distribution

Binomial Distribution

Normal Distribution


Standard Normal Distribution

T Distribution

Central Limit Theorem

Hypothesis Testing

Null and Alternative Hypothesis

Significant Level



Type I and Type II Error

A/B Testing With Practical Examples

Introduction to Machine Learning

Supervised and Unsupervised learning

Introduction to scikit-learn

Understanding Classification problems, regression problem, dependent and independent variables

Train, Test and Optimize regression and Classification Models

Supervised Learning

Linear Regression

Logistic Regression

Decision Tree

Introduction to NLP and Lexical Processing

Unsupervised Learning: Clustering

Introduction to clustering problems

K-Means Clustering

Other Types of Clustering

Forecasting Algorithms

Introduction to Time series Forecasting

Different Forecasting Models

Introduction to Git and GitHub

Introduction to Version Control System

Git Essentials

Git Commands and Functionalities

Create Your First Project

Random Forests and Bagging

Bagging for Imbalanced Classification

Random Forest for Imbalanced Classification

Easy Ensemble for Imbalanced Classification



XG Boost

Gradient Boosting

Model Selection

Principles of Model Selection

Feature Engineering

Model Evaluation

Class Imbalance

Principal Component Analysis

Introduction to PCA

Vector Representation and Operation

Matrix Operation (Recap)

Dimensionality Reduction

Model Performance

Advanced Regression

Estimating Coefficients in SLR and MLR

Matrix representation of SLR and MLR

Assumption of Linear Regression

Identify Non-linear data

Polynomial Regression

Regularisation (Ridge and Lasso)

Introduction to Computer Vision

Image Detection/Handwriting Classifier: OpenCV Demo

Introduction to Neural Network

Convolutional Neural Network

How to Build CNN in Python Keras

Image Augmentation: Cats vs Dogs Classifier

Principles of Object Detection

TensorFlow Object Detection APIs

Dark Flow and YOLO: Object Detection

Style Transfer: Make AI Generated Art

Domain-based Capstone Projects- Learning Outcome

Problem Statement and Project Objectives

Approach for the Solution

Optimum Solutions

Evaluation Metrics

Gathering Actionable insights

Book Demo class

1200+ QualifyEd Students got their dream job
Let's hear them ...

QualifyEd not only helped me sharpen my Digital marketing skills but also connected me with incredible opportunities. The placement support was phenomenal, and now I'm thriving as a Digital Marketing Manager at IBM. I'm grateful for the invaluable experience and knowledge gained through QualifyEd.

Enrolling in QualifyEd's placement program was a game-changer for me. The personalized guidance and industry-focused curriculum prepared me for the real-world challenges. Today, I'm thriving as a Software Engineer at Capgemini, and I owe a huge thanks to QualifyEd for paving the way to my success.

I can't thank QualifyEd enough for the incredible journey. The hands-on training and mentorship played a pivotal role in shaping my career. Today, I'm making a real impact as a Data Scientist at Mu sigma. QualifyEd is not just an education provider, it's a career catalyst.

Choosing QualifyEd was one of the best decisions I made for my career. The placement program was a perfect blend of theory and practical skills. The result? I'm now a UX/UI Designer at Ericsson, turning my passion into a profession. Thank you, QualifyEd, for making my dreams a reality

The QualifyEd placement program exceeded my expectations. The industry-relevant curriculum, coupled with expert guidance, propelled me into a fulfilling career as a Data Analyst at Absolutdata. Grateful for the skills acquired and the doors QualifyEd opened for me.

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Next Batch
Reserve your Seat

Demo class

      25th June

Counselling session

      28th June

Batch Start

      01st July

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