About Digital Lync

Digital Lync
Data Science Training in Hyderabad
Fundamentals of Data & IT
Python for Data Science
Math & Stat for Data Science
Machine Learning
Deep Learning
Artificial Intelligent (AI)
Cloud & DevOps for Data Science
  • Online & ClassRoom Real-Time training
  • Project & Task Based Learning
  • 24/7 Learning Support with Dedicated Mentors
  • Interviews, Jobs and Placement Support
50000 + Students Enrolled
4.7 Rating (500) Ratings
60 Days Duration
DevOps

Why Data Science Program ?

8 LPA Avg package
44 % Avg hike
3000 + Tech transitions

5k

2k

5k

1k
0k

Anual Average Salaries

Min (6L)
Avg (15L)
Max (30L)
Demand
Demand
70%

Managers said
hiring Fullstack engineers
was top priority

9 LPA Avg package
46 % Avg hike
4000 + Tech transitions

5k

2k

5k

1k
0k

Anual Average Salaries

Min (4L)
Avg (12L)
Max (25L)
Demand
Demand
87%

Managers said
hiring Fullstack engineers
was top priority

10 LPA Avg package
48 % Avg hike
2000 + Tech transitions

5k

2k

5k

1k
0k

Anual Average Salaries

Min (8L)
Avg (15L)
Max (40L)
Demand
Demand
80%

Managers said
hiring Fullstack engineers
was top priority

9 LPA Avg package
48 % Avg hike
3000 + Tech transitions

5k

2k

5k

1k
0k

Anual Average Salaries

Min (97L)
Avg (15L)
Max (20L)
Demand
Demand
83%

Managers said
hiring Fullstack engineers
was top priority

8 LPA Avg package
44 % Avg hike
3000 + Tech transitions

5k

2k

5k

1k
0k

Anual Average Salaries

Min (7L)
Avg (16L)
Max (30L)
Demand
Demand
87%

Managers said
hiring Fullstack engineers
was top priority

7 LPA Avg package
46 % Avg hike
3000 + Tech transitions

5k

2k

5k

1k
0k

Anual Average Salaries

Min (9L)
Avg (18L)
Max (40L)
Demand
Demand
87%

Managers said
hiring Fullstack engineers
was top priority

Our Alumni Work at Top Companies

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Explore the Digital Lync way
1

Learn

Learn from Curated Curriculums developed by Industry Experts

Data Science Curriculum

It stretches your mind, think better and create even better.
Fundamentals of IT and Data

Introduction to Information Technology in Data Science

Computer Science versus Information Technology: Orientation for Data Scientists

Fundamentals of Data Storage, Memory, and Processing Systems

Defining Data Science: Scope and Applications

Relationship between Data Science, Machine Learning, and Artificial Intelligence

Overview of the Data Science Lifecycle: From Problem Definition to Solution Deployment

Database Fundamentals for Data Scientists

Comparative Analysis: SQL versus NoSQL

Introduction to Cloud Databases and Data Warehousing Solutions

Essential Data Structures for Data Science

Introduction to Algorithms in Data Science

Understanding Complexity and Big O Notation

Data Types: Structured versus Unstructured Data

Working with Popular Data Formats: CSV, JSON, XML

Introduction to Data Extraction: Methods and Best Practices

Python for Data Science

Python Language Basics: Variables, Conditions, and Functions

Advanced Python Structures: Lists, Tuples, Dictionaries

Virtual Environments and Package Management in Python for Data Science

NumPy for Numerical Data Processing

Pandas for Data Wrangling and Analysis

Introduction to Data Cleaning Techniques with Python

Visualizing Data with Matplotlib and Seaborn

Advanced Data Visualization Techniques

Interactive Data Visualizations with Plotly and Dash

Web Scraping with Python: Beautiful Soup and Scrapy

Utilizing APIs for Data Collection

Strategies for Working with Cloud Data in Python

Object-Oriented Programming in Python

Writing Efficient and Readable Python Code

Error Handling, Debugging, and Unit Testing in Python

Mathematics and Statistics for Data Science

Introduction to Vectors, Matrices, and Operations

Eigenvalues and Eigenvectors: Concepts and Applications

Scalars, Vectors, and Tensors: Understanding through Linear Algebra

Fundamentals of Differentiation and Integration in Data Science

Understanding Gradient, Gradient Descent, and Cost Functions

Applications of Calculus in Machine Learning and AI

Foundations of Probability Theory

Descriptive Statistics and Inferential Statistics

Statistical Measures, Distributions, and Hypothesis Testing

Regression Techniques and Their Applications

Analysis of Variance (ANOVA) and Its Use Cases

Implementing Time Series Analysis in Data Science Projects

Understanding Sampling Techniques and Methodologies

Principles of Experimental Design

Conducting A/B Testing and Result Interpretation

Machine Learning

Concepts in Supervised, Unsupervised, and Reinforcement Learning

Overfitting, Underfitting, and Model Validation Techniques

Cross-Validation and Hyperparameter Tuning

Overview of Classification Algorithms

Decision Trees, Random Forests, and Gradient Boosting Machines

Model Evaluation Metrics and Techniques

Linear Regression and Its Variants

Understanding Polynomial Regression and Regularization Techniques

Performance Evaluation in Regression Models

Clustering Techniques: K-Means, Hierarchical, and DBSCAN

Introduction to Principal Component Analysis (PCA)

Association Rule Mining: Concepts and Applications

Ensemble Methods: Bagging, Boosting, and Stacking

Feature Engineering and Selection

Introduction to Advanced Algorithms: Neural Networks and SVMs

Deep Learning

Basics and Anatomy of Neural Networks

Activation Functions: Types and Their Impact

The Training Process: Backpropagation and Learning Rates

Getting Started with TensorFlow: Installation and Basics

Building Models with Keras: A Gentle Introduction

PyTorch for Deep Learning: Key Features and Differences

Fundamental Concepts of CNNs and Their Architecture

Implementing a CNN for Image Recognition Tasks

Advanced Techniques: Transfer Learning and Fine-tuning

Topics

Understanding RNNs: From Basics to LSTM Networks

Sequence Prediction and Text Generation with RNNs

Challenges and Solutions: Vanishing Gradients and Long-term Dependencies

Exploring Generative Adversarial Networks (GANs)

Autoencoders for Feature Learning and Generation

Reinforcement Learning Basics: Building Intelligent Agents

Artificial Intelligence

The Landscape of AI: Defining AI and Its Domains

Rule-based AI vs. Machine Learning-driven AI

Evolution and Key Milestones in AI

Introduction to Text Processing and Analysis

NLP Techniques: From Tokenization to Semantic Analysis

Leveraging NLP Libraries: NLTK, spaCy, and Beyond

Fundamentals of Computer Vision with AI

Implementing Object Detection and Recognition Systems

Advanced Applications: Facial Recognition and Autonomous Vehicles

Ethical AI Development: Challenges and Best Practices

Data Privacy and Security in AI Implementations

The Future of Work and Society with AI

General AI vs. Narrow AI: Understanding the Scope

AI in Robotics: Current State and Future Prospects

The Role of AI in Shaping Future Technologies

DevOps for Data Science

Overview and Importance of DevOps in Data Science

Implementing Continuous Integration (CI) and Continuous Deployment (CD) in ML

Containerization with Docker: Basics for Data Scientists

Cloud Platforms for Data Science: AWS, Azure, and GCP

Deploying and Managing ML Models in the Cloud

Utilizing Cloud-based ML Services for Scalable Solutions

Introduction to MLOps Practices and Tools

Monitoring and Version Control for ML Projects

Managing the Lifecycle of ML Models in Production

Big Data Technologies for ML: Hadoop, Spark, and Beyond

Building Scalable ML Models on Big Data Platforms

Challenges and Solutions in Large-scale ML Deployment

Understanding Data Governance and Compliance

Best Practices for Ethical AI and ML

Navigating Regulatory Requirements for Data Science Projects

2

Build

Work on our Real-time Projects , Task Based

LMS Project

LMS Project

An LMS project develops a digital platform for online learning, featuring course creation, content management, user tracking, assessments, and reporting, aimed at enhancing educational interaction.

HRMS Project

HRMS Project

The HRMS project develops a digital system for managing HR functions like employee data, payroll, recruitment, and performance, aiming to streamline processes and enhance organizational efficiency.

CRM Project

CRM Project

A CRM project develops a system to manage company interactions with customers, incorporating tools for contact, sales, productivity, and support to enhance service, drive sales, and boost retention.

3

Get Certification

Internships and Course certifications for Enhanced Skill Validation.

Internship Certificate

Certificate

Course Completion Certificate

Certificate
4

Get Job

Our focus on job-readiness Github Profile, Linkedin Profile, Resume Prep and Help Apply

  • GitHub Profile

    Guidance on creating and maintaining a professional GitHub profile to showcase technical projects and coding prowess.

  • LinkedIn Profile

    Assistance in crafting a compelling LinkedIn profile for networking and visibility among recruiters.

  • Resume Preparation

    Expert advice on resume writing to effectively highlight skills, experience, and achievements.

  • Help in Applying

    Support in identifying suitable job opportunities and navigating the application process.

Globe

IT Engineers who got Trained from Digital Lync

Satish Korlapati

Senior Associate Consultant
DevOps engineers

Raveena Reddy

SRE/DevOps Engineer
DevOps engineers

Akhil Nagothu

Cloud Devops Engineer-2
DevOps engineers

Vijay Kumar Putturu

Cloud Devops Engineer
DevOps engineers

Upcoming Batch Schedule

Week Day Batches
(Mon-Fri)

25th Sept 2023
Monday

8 AM (IST)
1hr-1:30hr / Per Session

Week Day Batches
(Mon-Fri)

27th Sept 2023
Wednesday

10 AM (IST)
1hr-1:30hr / Per Session

Week Day Batches
(Mon-Fri)

29th Sept 2023
Friday

12 PM (IST)
1hr-1:30hr / Per Session

Can’t find a batch you were looking for?

Why Digital Lync

50,000+ Learners
5000+ Batches
10+ Years
24/7 Support

Learn. Build. Get Job.

50,000+ uplifted through our hybrid classroom & online training,
enriched by real-time projects and job support.

Our Locations

Come and chat with us about your goals over a cup of coffee

Locations
Hyderabad, Telangana

2nd Floor, Hitech City Rd, Above Domino's, opp. Cyber Towers, Jai hind Enclave, Hyderabad, Telangana,

Locations
Bengaluru, Karnataka

3rd Floor, Site No 1&2 Saroj Square, Whitefield Main Road, Munnekollal Villag Post, Marathahalli, Bengaluru, Karnataka

Locations
Kakinada, Andhra

Madhav Nager Main Road, Opp SBI Bank, Opp SP Office, Kakinada,
Andhra Pradesh

Call Us