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Full Stack Data Science

Full Stack Data Science

Full Stack Data Science refers to the comprehensive skill set needed to work with data across the entire data science pipeline. It includes expertise in data acquisition, cleaning, analysis, modeling, and visualisation, along with programming, statistics, and machine learning. Full stack data scientists can handle end-to-end projects, from data collection to deploying models, and have strong communication and problem-solving abilities.

4.5 Rating

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Course Features
Comprehensive Data Science Curriculum: Extensive coverage of all aspects of data science
Instructor Lead live Class
One-Year Internship: Opportunity for a year-long internship to gain real-world experience
Live teaching by experienced instructors for interactive sessions
Hands-On Industry Projects: Engage in over 56 industry real-time projects for practical experience.
450+ Hours of Live Classes: Extensive live classes for in-depth learning and clarification of concepts.
Lifetime Dashboard Access: Access to course materials and resources even after course completion
Module Assignments: Assignments provided for every module to reinforce learning and assess progress
Internal Hiring
What you'll learn?
Programming Language: Python
Statistics: Stats
Algorithmic Modeling: Machine learning
Neural Networks: Deep learning
Image Analysis: Computer vision
Text Analysis: Natural language processing
Data Insights: Data analytics
Large-scale Data Processing: Big data
System Design: Architecture
Data Storage: Databases
Prerequisites
System with Internet Connection
Computer/Laptop with min 4 GB of RAM
Dedication
Interest to Learn
Extra skills you'll learn by choosing SKOLIKO
Project Management
Strategic Thinking
Tech-Savvy Mindset
Professional CV Crafting
Interview Preparation
Networking with Industry Experts.
Career Development
Organizational Culture
Certificate

GET CERTIFICATE | GET PLACEMENT IN TOP COMPANIES

Upon successful completion of this course and all assessments, you'll earn a valuable certificate. This credential formally validates your newly acquired skills and knowledge, serving as a tangible testament to your dedication and achievement in this field.

SKOLIKO is an innovative leader in the education industry, committed to bridging the divide between academic and professional spheres.

Embrace change, pursue growth

relentlessly, and let your passion drive

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MODULES

Introduction

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Introduction to Python

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Advanced Concepts in Python Programming

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Overview of Database Integration with Python

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Overview of Data Manipulation with Pandas and Numpy

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Introduction to Graphical User Interface (GUI) Programming

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Overview of Data Visualization

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Introduction to Application Programming Interfaces

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Overview of Python Project Development

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Overview of Exploratory Data Analysis (EDA)

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Introduction to Machine Learning

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Overview of an End-to-End Machine Learning Project

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Introduction to Principal Component Analysis (PCA) in Machine Learning

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Introduction to Natural Language Processing (NLP) in Machine Learning

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Overview of Time Series Analysis in Data Science

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Statistics

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Overview of Machine Learning Projects

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ML Project 1 - Fault detection in wafers based on sensor data

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ML Project 2 - Cement Strength Prediction

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ML Project 3 - Credit Card Defaulters

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Time Series

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Introduction to Deep Learning

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DL ANN - Perceptron

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DL ANN - Perceptron

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DL ANN - 2

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DL ANN - 3

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DL ANN - 4

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DL ANN - 5

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Computer Vision - Introduction

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Computer Vision - CNN Foundations

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Computer Vision - CNN Architectures

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Computer Vision - Image Classification Hyper

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Computer Vision - Data Augmentation

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Computer Vision - Object Detection Basics

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Computer Vision - Object Detection Architectures

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Computer Vision - Practical's Object Detection using TensorFlow 1.x

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Computer Vision - Practicals Training a Custom Cards Detector using Tensorflow1.x

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Computer Vision - Practical’s Creating a Cards Detector Web App with TFOD1

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Computer Vision - Practicals Object Detection using TensorFlow 2.x:

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Computer Vision - Practicals Training a Custom Chess Piece Detector using TensorFlow 2

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Computer Vision - Practicals Creating a Chess Piece Detector Web App with TensorFlow 2

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Computer Vision - Practicals Object Detection using Detectron2

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Computer Vision - Practicals Training a Custom Detector using Detectron2

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Computer Vision - Practicals Creating a Custom Detector Web App with Detectron2

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Computer Vision - Practicals Object Detection using YoloV5

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Computer Vision - Practicals Training a Custom Warehouse Apparel Detector using YOLOv5

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Computer Vision - Practicals Creating a Warehouse Apparel Detector Web App with YOLOv5

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Computer Vision - Image Segmentation

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Computer Vision - MASK RCNN Practicals with TFOD

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Computer Vision - MASKRCNN practical with Detectron2

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Computer Vision - Face Recognition Project

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Computer Vision - Object Tracking Project

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Computer Vision - GANS

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Computer Vision Project - Traffic Vehicle Detection

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Computer Vision Project - Helmet Detection

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Computer Vision Project - Fashion Apparel Detection

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Computer Vision Project - Image to Text OCR

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Computer Vision Project - Shredder System:

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Computer Vision Project - Automatic Number Plate Recognition with TFOD1.x

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NLP Overview

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NLP Word Embeddings

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NLP RNN

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NLP LSTM & GRU

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NLP Attention Based Model

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NLP Transfer Learning in NLP

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NLP Project: - Megatron

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NLP Project: - Text to Speech

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NLP Project: Speech to Text

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NLP Project: Spell Corrector

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Debugging the Application NLP Project: Named Entity Recognition (NER)

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NLP Project:- Machine Translation & Keyword Spotting

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NLP Project:- Keyword Extractor & Summarization

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NLP project: - Paraphrasing

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BigData

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MapReduce & YARN in Big Data

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BigData - Hive

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NoSQL and HBase in Big Data

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BigData - Sqoop

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Spark - Overview and Introduction

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BigData - Spark ML

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Spark Streaming

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Kafka - Introduction

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Apache Airflow

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Big Data Projects

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Exploring Basic Charts in Power BI Desktop

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Building Interactive Maps in Power BI

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Table and Matrix Overview

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Different Charts in Power BI Overview

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Cards and Filters

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Slicers in Power BI Overview

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Introduction to Tableau

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Different charts in Tableau

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Database Architecture-SQL

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Introduction to Excel

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Course duration - 450 Hours

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Course day - every week “Saturday”

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Course time - 04:00pm to 07:30pm

Vincent Thomas Varghese
Instructor
Vincent Thomas Varghese

Experienced TechnoStrategist

4.5 Rating

Experienced Technostragist with three decades in IT, excelling in Sales, Product Management, and Marketing across IT hardware, networking, and software. Proven strategic planner, startup pioneer, and mentor for large teams. Marketing authority in areas such as Business Incubation, Branding, and Sales. Vast industry expertise spans ITES, IT Hardware, IT Training (Software), Distribution, and Retail. Recognized for interpersonal leadership, intuitive decision-making, and a collaborative approach. Complemented by four years as a Data Scientist, enhancing analytical and problem-solving skills with a deep passion for coding and a knack for simplifying complex concepts,

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