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  Learn Data Analytics  

Professional Data Analytics Online Course

Expert-led Data Analytics Training

Industry-recognized certification

Hands-on projects and real-world case studies.

Flexible online learning

Internship

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Upcoming Class Schedule

Feb 15th 2025

6PM - 9PM

Graduates & Early to Mid-career Professionals

Duration

120 Hours

Mode

Online

Format

Hands-On Training

Suited For

Graduates & Early to Mid-career Professionals

Each weeks

4 Weeks

Each Session

6 Sessions

Instructor

Gaythri T

Gaythri T

Subject Matter Expert - Data Analytics

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Why Learning Data Analytics Online Course is the Best Decision?

Data Analytics prepares graduates and professionals with skills to analyze data, extract insights, and enhance decision-making, opening doors to career growth in data-driven industries.

Skill-Up Introduction to Data Analytics Course Specialized for Graduates and Professionals in Dubai.

As a global business hub, the UAE highly demands certified data analytics professionals. Our Data Analytics course, considered the best statistics course for data analytics provides the skills you need to succeed in this booming industry.

High Demand

Companies are actively hiring for roles that require expertise in data sources and visualization.

Future-Proof Skills

Companies are actively hiring for roles that require expertise in data sources and visualization.

Tools That Matter

Get hands-on experience with Power BI, Data Visualization Tableau, and SQL to stay ahead.

Take the Leap with KGiSL Skill Development Training Institute

As a global business hub, the UAE highly demands certified data analytics professionals. Our Data Analytics course, considered the best statistics course for data analytics provides the skills you need to succeed in this booming industry.

Ready to Switch your career?

In our Skillup data analytics course today.

Why Choose KG Skill Development's Data Analytics Course

200+ Hours of Live Sessions

180+ Hours of Project

180+ Hours of Self-Practice

25+ Aptitude Tests

EPIC Learning

Adaptive LMS

Soft Skills Training

Ongoing Career Support

Flexible EMI Plans

Data Analytics Course Overview

From mastering basic SQL to diving deep into data transformation techniques, this course lays the foundation for understanding data sources and utilizing powerful tools like Power BI and Tableau.

From Graduate to Successful Data Analyst

For Graduates: Start your data analyst career with beginner-friendly modules:

For Mid-Career Professionals: Advance your career with data analytics:

Data Analyst Course Curriculum

Crafted with over 25 years of expertise to deliver comprehensive knowledge and practical skills in data analytics.

Module 1

Overview:

This module focuses on mastering Microsoft Excel for data analysis. Students will learn key functionalities, from formulas to advanced features like macros and Power Pivot, essential for creating dashboards and generating insights.

Areas of Study:

Microsoft Excel Basics

Learn the essentials of Excel, including navigation and basic operations.

Formulas & Functions

Understand and apply various formulas and functions to analyze data efficiently.

Pivot Tables

Gain expertise in summarizing, analyzing, and presenting data using pivot tables.

Dashboards and Insights Writing

Design interactive dashboards and write actionable insights.

Data Analysis Using Excel

Utilize Excel's tools for in-depth data analysis.

Macros

Automate repetitive tasks using macros.

Power Pivot

Analyze large datasets and build sophisticated data models.

Outcomes:

Proficiency in advanced Excel features for data analysis.

Ability to create professional dashboards and derive actionable insights.

Foundational knowledge for advanced analytics tools.

Module 2

Overview:

This module provides a strong foundation in database management using MySQL. Students will learn to manipulate, query, and manage relational databases effectively.

Areas of Study:

DBMS Introduction and Basics of MySQL

Understand database fundamentals and MySQL basics.

Data Types and Keys

Learn about different data types and the concept of primary and foreign keys.

SQL Sub-Languages

Master DML, DDL, DQL, DCL, and TCL commands.

Functions

Apply date/time, string, and arithmetic functions.

Joins and Set Operations

Perform complex queries using joins and set operations.

Subqueries and Views

Work with nested queries and create database views.

Procedures and Triggers

Automate processes using stored procedures and triggers.

Normalization

Learn normalization techniques to optimize database design.

Outcomes:

Expertise in SQL for managing and querying databases.

Ability to write complex queries and optimize database performance.

Knowledge of advanced SQL concepts like procedures and triggers.

Module 3

Overview:

This module covers essential statistical concepts used in data analysis, including descriptive and inferential statistics, regression, and hypothesis testing.

Areas of Study:

Descriptive Statistics

Learn measures of central tendency and variability.

Probability Theory

Understand the fundamentals of probability.

Inferential Statistics

Perform sampling, estimation, and hypothesis testing.

Hypothesis Testing

Test assumptions using statistical methods.

Regression Analysis

Analyze relationships between variables and predict outcomes.

Outcomes:

Strong foundation in statistical techniques for data analysis.

Ability to perform hypothesis testing and interpret results.

Proficiency in regression analysis for predictive modeling.

Module 4

Overview:

This module focuses on creating data visualizations and dashboards using Tableau, a leading business intelligence tool.

Areas of Study:

Introduction to Tableau

Learn the basics of Tableau and its interface.

Charts and Visualizations

Create basic and advanced charts.

Pivoting and Transforming Data

Prepare and transform data for analysis.

Working with Time Series Data

Analyze trends and patterns over time.

Performing Calculations

Use calculated fields for dynamic analysis.

Customizing Reference Lines and Maps

Integrate Mapbox for geospatial visualizations.

Designing Interactive Dashboards

Build engaging dashboards.

Principles of Effective Data Storytelling

Convey insights effectively using visualizations.

Outcomes:

Mastery of Tableau for data visualization.

Ability to create interactive dashboards and tell compelling stories with data.

Get hands-on experience in transforming data and building advanced visualizations.

Module 5

Overview:

This module covers Power BI, a powerful tool for business intelligence, focusing on data transformation, visualization, and dashboard creation.

Areas of Study:

BI Components

Understand the components of business intelligence.

Connecting to Various Data Sources:

Learn to connect and import data.

Datasets and Dataflows

Manage and utilize datasets effectively.

Power Query Editor

Transform data for analysis.

Data Transformation Techniques

Clean and prepare data for reporting.

Introduction to DAX

Write basic and advanced expressions in DAX.

Charts and Visualizations:

Create and customize visualizations.

Advanced Visualization Techniques

Explore sophisticated visualization methods.

Report and Dashboard Creation

Design comprehensive dashboards.

Outcomes:

Expertise in Power BI for business intelligence.

Ability to clean, transform, and visualize data effectively.

Skills in creating professional reports and dashboards.

Skills You’ll master

Allows your business and technology computers to store, transmit, analyze, and manipulate big data.

Data Cleaning & Transformation

SQL Querying & Management

Data Visualization (Tableau, Power BI)

Statistical Analysis & Testing

Predictive Modeling & Machine Learning Basics

Advanced Excel for Analytics

Data Interpretation & Insights

Business Intelligence Tools

Data-Driven Decision Making

Report Writing & Storytelling

Explore Career Growth

Data analytics is not just about crunching numbers—it's about solving problems and driving decisions. Enroll in this course to get the skills for a successful data analyst career and endless opportunities.

Dubai’s Booming Data Analyst Job Market

Dubai’s Booming Data Analyst Job Market

Opportunities abound in industries such as:

Our courses are customized to prepare you for beginner data analyst jobs and prepare you for long-term career growth.

Flexible Learning for Busy Professionals

Flexible Learning for Busy Professionals

We understand the fast-paced lifestyle in Dubai. Our data analysis online course with certificate offers:

Career Progression for Mid-Career Professionals

Career Progression for Mid-Career Professionals

As Dubai embraces digital transformation, mid-career professionals can leverage data analytics to:

Master Data Analytics with Real-World Projects

Sharpen your data analytics skills with hands-on projects that cover everything from data visualization to predictive modeling, preparing you for top industry roles.

Financial Dashboard Creation with Pivot Tables and Macros

Financial Dashboard Creation with Pivot Tables and Macros

Design a dynamic financial dashboard with pivot tables, interactive charts, and macros that analyze and visualize company performance, providing actionable insights.

Regression Analysis for Customer Sales Prediction

Regression Analysis for Customer Sales Prediction

Apply regression analysis techniques to predict customer sales behavior, and perform hypothesis testing to evaluate the effectiveness of marketing strategies.

Retail Store Database Design and Query Optimization

Retail Store Database Design and Query Optimization

Develop a robust database system for a retail store, implementing normalized tables, complex queries, and stored procedures to ensure efficient data management and retrieval.

Interactive Sales Performance Dashboard

Interactive Sales Performance Dashboard

Build a time-series sales performance dashboard, integrating data from multiple sources and utilizing Mapbox for geographic insights, while leveraging data storytelling for impactful visualizations.

Business Intelligence Dashboard with DAX and Data Transformations

Business Intelligence Dashboard with DAX and Data Transformations

Create a sophisticated business intelligence dashboard by connecting to multiple data sources, transforming data for advanced analytics, and using DAX for custom calculations and metrics.

Outcomes of completing our Data Analytics course

Stay Ahead of Industry Trends

Stay Ahead of Industry Trends

Data analytics is a rapidly growing field, and gaining expertise in this area will ensure you stay ahead of the curve, making you more competitive in the job market.

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Build a Strong Data Analytics Portfolio

Build a Strong Data Analytics Portfolio

Work on real-world data analytics projects to build a portfolio that demonstrates your skills in data collection, analysis, and visualization, which can help you stand out to employers.

 Intern with Leading Companies

Intern with Leading Companies

Eligible learners can get a 1-month internship opportunity with top companies post-course, where you'll work on industry-specific data analytics projects and gain hands-on experience.

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 Better career Opportunities

Better career Opportunities

By completing the Data Analytics course, you open doors to top careers such as Data Analyst, Business Analyst, Data Scientist, and Data Engineer.

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Data Analysis Online Course With A Certificate

Earn an industry-recognized Professional Certification in Data Analytics to highlight your expertise. Share your certification on LinkedIn or your network to unlock new opportunities in data-driven fields.

Ready to Get Started?

Frequently Asked Questions?

  • Beginners looking to explore a career in data analytics.
  • Professionals wanting to enhance their data-handling skills.
  • Students aiming to build a foundation in data analysis.
  • Entrepreneurs or business owners seeking insights from their data

As a beginner, focus on:

  • Excel: Learn Excel from beginner to advanced for effective data analysis.
  • Basic SQL: Learn SQL to query and manage databases.
  • Data Visualization: Learn tools like Power BI or Tableau.
  • Basic Statistics: Understanding data trends and patterns.
    Optional skills like Python or R can give you an edge.

Data analytics positions are among the most in-demand due to their crucial role in decision-making across various industries.

Data science, AI, and cloud engineering roles lead the way in terms of salary, though data analysts with specialized skills can also earn competitive wages.

 Proficiency in Power BI, Tableau, and SQL is crucial. Our data analytics Power BI module is tailored for practical applications.

 AI enhances analytics but cannot replace the human intuition and strategic thinking a data analyst brings.

The main pillars include data collection, cleaning, transformation, analysis, and visualization.

The duration of the course depends on your pace. On average, KGiSL Skill Development Training Institute’s online data analytics course takes between 5 to 6 months to complete, with self-paced modules that allow you to learn according to your schedule.

No, prior experience is not required. This Data Analytics course is designed for beginners, and we start with foundational concepts. However, familiarity with basic computer skills and an interest in problem-solving will be beneficial.

While the course equips you with the necessary skills, securing a job depends on your efforts, networking, and the job market. Our course prepares you with the practical skills that employers look for. We are here to help you with placements with right companies.

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GAYTHIRI-T
Subject Matter Expert - Data Analytics and Data Science
Educational Qualification:

Master of Science in Machine Learning & Artificial Intelligence | Liverpool John Moores University, UK

Executive PG Diploma: ML & AI | International Institute of Information Technology, Bangalore
Bachelor of Engineering in Computer Science | Thiagarajar College of Engineering, Madurai

Professional Summary

  • Over 5+ years of industrial and training experience including TCS
  • Implemented an automated customer complaint classification system, utilizing NMF for topic modelling on clients' complaints dataset and designing a supervised model to predict relevant topics for incoming complaints.
  • Implemented a Random Forest predictive maintenance model, chosen for robust performance and interpretability, in the manufacturing equipment's control system, utilizing sensor data to proactively identify issues and achieve a 28.7% reduction in equipment downtime.
  • Established an end-to-end Machine Learning Operations (MLOps) solution using Jarvislabs to lower the Customer Acquisition Cost (CAC) for EdTech firm 'CodePro' by computing lead scores to forecast course enrolment likelihood.
  • Developed a capstone project focusing on credit card fraud detection.
  • Assessed the loan dataset of a lending finance firm to determine the likelihood of a client defaulting or repaying a loan based on foundational client information.
  • Developed and led the implementation of a time series forecasting model, incorporating diverse models, including XGBoost and LSTM, resulting in a 16.3% reduction in energy load prediction errors.
  • Implemented a real-time fraud detection system in a cosmetic E-commerce platform using XGBoost, reducing fraudulent transactions by 18.8%, enhancing security and customer trust.
  • Innovated a gesture recognition feature for smart TVs, implementing a system adept at accurately identifying five user gestures from input videos using three architectures: 3D Convolutional network, CNN + RNN, and Transfer learning with GRU (Gated Recurrent Units), enabling seamless TV operation without a remote.
  • Implemented a robust quality control system utilizing sensor details and product images, integrating a finely tuned CNN model, resulting in a significant 21.4% reduction in product defects.
  • Established customer segmentation through K-Means clustering, crafting personalized marketing strategies, product recommendations, and tailored communication channels for each distinct customer group based on in-depth analysis of common characteristics, behaviors, and preferences.
  • Statistics essentials, Inferential statistics, Hypothesis testing
  • Exploratory Data Analysis, Predictive Analysis, Regression & Classification
  • Linear and Logistic Regression, Naive Bayes Classifier, Decision Trees, Random Forests, Bagging and Boosting Techniques, XGBoost, Clustering – K Means and Hierarchical clustering, Principal Component Analysis (PCA)
  • Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Transfer Learning, LSTM (Long Short-Term Memory networks), GRU (Gated recurrent units)
  • NLP (Natural Language Processing), MLOPs
  • Tools Excel, VSCode, Jupyter, Jarvislabs, GIT
  • Packages Python, Pandas, Numpy, Scikit Learn, Matplotlib, Seaborn
  • Data Exploration & Analysis, Model Building & Evaluation
  • Feature Engineering, Data Storytelling & Visualization
  • Machine Learning Model Selection, Predictive Modeling
  • Computer vision, Metaheuristic Optimization algorithms
  • Deep Learning
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