In today’s data-driven world, businesses use Data analytics to make important decisions, which is essential for their success and growth. With Data Analytics, organizations can make informed choices, contributing to their development. In India, the demand for a professional data analyst is very high because many people show interest in the data analysis field. The data analyst requires the fundamentals of the Data Analytics course structure that will enable him or her to unlock the full potential of the required course as they are taught the essential topics concerning the course. The Data Analytics course structure, therefore, provides guidelines to the learner about what necessary project to involve expertise such as Data structure, statistics, Data collection method, algorithms, Python programming, Machine learning, and more proficiencies in several needed Data analytics tools. Hence in the article below, we will provide the necessary guidelines the learner should know about the Data Analytics course structure. The guidelines would enable one to make a sound decision to secure an accurate education path.
Let us learn the meaning of data analytics before we guide you to the data analytics course structure.
What is Data Analytics?
Data Analytics you can uncover new business risks and opportunities you could never have known about otherwise.
Data analytics is a process of tools and technology that manages qualitative and quantitative data to discover new business risks and opportunities. Data analytics uses techniques from math, statistics, and computer programming to gain insights from data.
The Data analytics course consists of how to analyze data, develop various theories of data collection, and create various storage structures. The primary focus is to learn specifically the patterns and how to interpret the groupings in relation.
Data analytics helps companies or firms improve customer service, marketing strategies, and greater profits. It helps a business to be more agile and able to respond quickly to market challenges and stay ahead of competitors.
Importance and Benefits of Data Analytics
Nowadays most departments in organizations or institutions use Data analytics to verify present scenarios and predict future outcomes. Data analytics offers valuable understandings that can be used to enhance processes, products, and services. When business enhances their abilities to analyze data, they can make smart decisions that lead to smoother operations and ultimately boost overall performances. It’s like upgrading your navigating system to take the best routes, helping you reach your destination faster and with fewer hiccups. Understanding data is fundamental for professionals at all levels and aids them in making informed decisions and taking targeted actions. Furthermore, data–related careers are among the fastest-growing, reflecting the increasing demand for professionals capable of utilizing data to drive better business outcomes.
Reduce the Cost of Operations: By maximizing processes and allocating resources, Data Analytics can help reduce unnecessary expenses and identify cost-saving opportunities within the organization.
Predicts Future Trends: By using technologies like predictive analysis, businesses can create future-focused products and respond quickly to emerging market trends, thereby gaining competitive advantages over business rivals. The data analyzed can vary depending on the applications and may range from historical records or freshly processed real-time information. Furthermore, it may originate from a combination of internal systems and external data sources.
Strengthen Security: Companies use data analytics methods, such as parsing, analyzing, and visualizing audit logs, to look at past security breaches and find the underlying vulnerabilities. Data analytics can also be integrated with monitoring and alerting systems to quickly notify security professionals in cases of attempted breaches.
Manages Risks: Using Data analytics helps organizations spot and address risks by spotting irregularities, fraudulent activities, and possible compliance breaches. It’s like having radar that picks up on potential dangers, allowing for proactive measures.
Improves Decision-making: Furthermore, Data Analysis acts as a guiding light for decision-makers amidst a vast ocean of information. It empowers organizations to make decisions grounds on solid evidence rather than gut feelings or speculations. This translates to more successful business choices, whether it’s pinpointing the most effective marketing strategy, streamlining supply chains, or introducing new products. By dissecting data, decision–makers can evaluate the potential risks and rewards associated with different options, leading to more informed and ultimately better decisions.
Improving Business Performances: Data analytics provides organizations with metrics and key performance indicators (KPIs) to track progress, monitor performances, and evaluate the successes of business initiatives. This facilitates business in promptly addressing shifting marketing dynamics and confronting various operational hurdles.
Better & personalised customer experience: By sharing their data, customers expect companies to know them, form relevant interactions, and provide seamless experiences across all touch points. The capability to respond quickly and foster a sense of value for customer liabilities solely on advanced analytics. Data empowers the customization of interactions based on individuals’ customer traits, thereby enabling comprehension of their preferences and enabling personalized engagements across multi-service channels.
With various software or specialized systems, the Data Analytics Course Structure is a comprehensive instruction in data extraction, analysis, and manipulation. The Data Analytics Course Structure aims to teach students by covering subjects such as Mathematics and Statistics, Data Structures, Stimulation, Data Collecting, and Comparisons. Although the Data Analytics course structure varies from program to program or curriculum to curriculum, the following are some frequent Data Analytics topics:
1. Introduction to Statistical Analysis
Counting, Probabilities, and Probabilities Distributions
Sampling distributions
Estimations and Hypothesis testing
Scatter Diagram
ANOVA & Chi-Squared
Data Cleanings
Imputation techniques
Correlations
Regression
Introduction to Data Analytics
Data Analysis is a fundamental component of the Data Analytics course structure and describes a range of techniques and methodologies to extract insights from data.
Data Analytics Overview
Importance of Data Analytics
Types of Data Analytics
Descriptive Analytics
Diagnostic Analytics
Predictive Analytics
Prescriptive Analytics
Benefits of Data Analytics
Data Visualization for decision making
Data types, measures of central tendency
Measures of dispersion
Graphical techniques
Skewness
Box plots
Kurtosis
Descriptive stats
Sampling variation
Sampling funnels
Central limits theorems
Confidences intervals
2. Business Fundamentals
Incorporating business fundamentals into a Data Analytics Course structure is essential for preparing students to work on their analytical skills effectively in real-world business contexts. Here is how business fundamentals can be integrated into this course.
Introduction to Business Concept
Case studies with practical examples
Business Metrics and KPIs
Business – Intelligence tools
Communication & Presentation skills
Ethical and legal considerations
3. Text Analysis
Text Analysis also called text mining or natural language processing (NLP) an important part of the Data Analytics course structure. Here’s how Text Analysis is incorporated into this course structure.
In a Data Analytics course structure, the topics of data collection are crucial as they form the foundations for all subsequent analyses. Here’s how data collection can be incorporated into the course.
Introduction to Data Collections
Types of Data
Data sourcing
Data collections methods
Sampling technicalities
Data Qualities and Validities
Ethical considerations
Data Documentaries and Management
Hands-on data-collecting projects
5. Data Visualization
In a Data Analytics course structure, data visualization is a critical component that helps students effectively communicate insights derived from data analysis. Here’s how data visualizations can be integrated into the course.
Introduction to Data Visualizations
Principles of Data Visualization
Types of Visualizations
Visualization tools
Data preparations for visualizations
Interactive Visualizations
Dashboards Design
Color Theory and Designs
Storytelling with Data
Hands-on Data visualization projects
6. Tools to Expertise in Data Analysis
Mastery of diverse data analysis tools is very essential for success in the field. Here are some pivotal tools:
SQL (Structured Query Language) is a powerful tool for data analysis, especially when working with large datasets stored in relational databases. Here’s how SQL fits into this course.
Introduction to Oracle Databases
Retrieving Data using SQL SELECT statements
Learn to Restricts and sort data
Single-row functions transform data in databases to customize the outputs.
Invoke Conversion Functions and conditional expressions.
Aggregate Data using Groups Functions
To showcase data from multiple tables using joins
Use Sub-Queries to solve queries
The SET operators
Data Manipulating statements
Use of Data Definitions Language (DDL) Statements to create and manage tables
Others Schemas Objects
Controls users’ access
Management of the Schema Objects
Manages Objects with Data Dictionaries views
Manipulates large data sets
Data Management in different time zones
Retrieving Data using Sub-queries
Regular Expression support
8. Tableau
Tableau is a powerful data visualization tool that is widely used in data analysis due to its intuitive interfaces and robust features. Here’s how Tableau contributes to the Data Analytics course structure:
Module 1: Tableau Course Material
Starts Page
Show Me
Connecting to Excel Files
Connecting to Textual Files
Connectivity to Microsoft SQL Servers
Connecting to Microsoft Analysis Services
Creating and Removes Hierarchies
Binning
Joins Tables
Data Blending
Module 2: Learn Tableau Basics Reports
Parameters
Grouping Examples 1
Grouping Examples 2
Editing’s Groups
Sets
Combined Sets
Creating a First Reports
Data Labeling
Create Folders
Sorting Data’s
Adding Totals, Sub Totals, and Grand Totals to Reports
Module 3: Learn Tableau Charting
Areas Chart
Bars Chart
Boxes Plot
Bubble Chart
Bump Charts
Bullet Graph
Circle Views
Dual Combination Charts
Dual Lines Charts
Funnels Chart
Traditional Funnels Charts
Gantt Chart
Grouped Bar or Side by Side Bars Chart
Heatmaps
Highlights Tables
Histogram
Cumulative histogram
Line Charts
Lollipops Charts
Pareto Charts
Pie Charts
Scatter Plots
Stacked Bar Charts
Text Labels
Tree Mapping
Word Cloud
Waterfall Charts
Module 4: Learn Tableau Advanced Reports
Dual Axis Reports
Blended Axis
Individual Axis
Adds Reference Lines
Reference Bands
Reference Distribution
Basic Mappings
Symbol Mapping
Uses Google Mapping
Mapbox Maps as a Background Map
Web Map Server Map as a Background Map
Module 5: Learn Tableau Calculating & Filtering
Calculated Fields
Basics Approaches to Calculating Ranks
Advancement Approaches to Calculating Rank
Calculating Running Totals
Filters Introduction
Quick Filters
Filters on Dimensions
Conditional Filters
Tops and Bottoms Filters
Filters on Measures
Context Filters
Slicing Flitters
Data Source Filters
Extract Filters
Module 6: Learn Tableau Dashboards
Create a Dashboard
Format Dashboard Layout
Create a device preview of a dashboard
Create Filters on Dashboard
Dashboard Objects
Creates a Story
Module 7: Server
Tableau online
Overview of Tableau Server
Publishing Tableau objects and Scheduling/Subscriptions.
Power BI is a powerful business intelligence tool and it is developed by Microsoft that facilitates data analysis, visualizations, and sharing of insights across organizations. Here’s how Power BI contributes to the course structure:
Module 1: Introduction to Power BI
Get started with Power BI
Overviews: Power BI concepts
Sign up for Power BI
Overviews: Power BI data source
Connect to a SaaS Solution
Upload a local CSV File
To connect Excel data that can be refreshed
Connects to a sample
Creates a report with visualizations
Explore the Power BI portal
Module 2: Viz and Tiles
Overviews: Visualizations
Using visualizations
Creating new reports
Create and arrange visualizations
Format a visualization
Creates chart visualization
Use map, text & gauze visualizations to save reports
Use a slicer to filter visualizations
Sort, copy, and paste visualizations
To Download and use custom visuals from the gallery
Module 3: Reports and Dashboards
Modify and Print a Report
Rename and delete report pages
Add filter to page or report
Set visualization interactions
Print a report page
Send a report to PowerPoint
Create a Dashboard
Create and manage the dashboards
Pin report tile to the dashboard
Pin live report page to the dashboard
Pin a tile from another dashboard
Pin Excel element to the dashboard
Manage pinned elements in Excel
Add a tile to a dashboard
Build a dashboard with Quick Insights
Set a Featured (default) dashboard
Ask Questions about Your Data
Ask a question with Power BI Q&A
Tweak your dataset for Q&A
Enable Cortana for Power BI
Module 4: Publishing Workbooks and Workspace
Share Data with Colleagues and Others
Publish a report to the web
Manage published reports
Share a dashboard
Create an app workspace and add users
Use an app workspace
Publish an app
Create a QR code and share a tile
Embed a report in SharePoint Online
Module 5: Power BI Components and Table Relationship
Use Power BI Mobile Apps
Get Power BI for mobile
View reports and dashboard in the app
Use workspaces in the mobile app
Sharing from Power BI Mobile
Use Power BI Desktop
Install and launch Power BI Desktop
Get data
Reduce data
Transform data
Relate tables
Get Power BI Desktop data with the Power Business Intelligence service
Extract report from Power BI to Desktop
Module 6: DAX functions
New Dax functions
Date and time functions
Time intelligence functions
Filter functions
Information functions
Logical functions
Math & trig functions
Parent and child functions
Text functions
10. Python
Python is a versatile programming language widely used in data analysis due to its rich ecosystem of libraries and tools. Here’s how Python contributes to the course:
The print statement
Comments
Python Data Structures & Data Types
String Operations in Python
Simple Input & Output
Simple Output Formatting
Deep copy
Shallow copy
Operators in python
11. R Programming
R is a powerful programming language and environment specifically designed for statistical computing and Data Analysis. Here is how R contributes to the Data Analytics course structure:
Background and Nuts & Bolts
Programming
Loop functions and Debugging
Simulation
Profiling
FAQs
1. Who is eligible to do the data analytic course?
Data Analytics courses structured in a way that suits all whether he or she’s Undergraduate, Graduate, or also can be working professionals anyone, who want to ameliorate their chops and are willing for a career in the analytics sphere.
2. What is the advantage of doing a data analytics course?
Today the world is driven by data for all age groups and the need for Data Analytics Courses is growing fleetly. So people earn plenty of money through completing the data analytics course.
3. What knowledge do we get during the course?
Students will acquire knowledge of Tableau, Excel, Python, SQL, R, PowerBI, QlikView, SAS, and Visualization tools and packages.
4. What are the career opportunities available for data analysts?
The career opportunities available are Data Analyst, Actuary, Statistician, Biostatistician, Market Research Analyst and Financial Consultant.
Conclusion
Finally, the Data Analytics course structure presented here offers a detailed and dynamic framework for aspiring data professionals. The Data Analytics course structure is for all whether he or she’s an Undergraduate, Graduate, or also can be working professional anyone, who wants to ameliorate their chops and is willing for a career in the analytics sphere.
Through a blend of theoretical knowledge and practical applications, students gain a deep understanding of the principles, tools, and techniques essential for analyzing complex databases and deriving actionable insights. The modular approach ensures flexibility, allowing learners to tailor their learning journey according to their interests and career goals.
Embracing the power of data, they become catalysts for positive change, shaping a future where informed decisions drive success. As we navigate towards a Data-centric world, the knowledge and skills acquired through this course pave the way for endless possibilities, empowering individuals to turn data into insights into insights into impact.
Strong data analysis skills and the ability to conclude from large data sets are prerequisites for employment as a data analyst. With the help of Analytics, raw data may be transformed into actionable intelligence by being organized into useful rows and columns that facilitate data processing, storage, analysis, and trend identification. Data Analysts are in high demand in Greece, as the nation’s IT industry continues to grow. If you wish to hone these abilities, you should look for these data analytics courses in Greece to help you meet the standards.
But, before we begin with the top data analytics courses in Greece let us understand data analytics in brief.
Defining Data Analytics?
Data Analytics entails deconstructing and analyzing data into Business Intelligence to keep in contact with customers. Large-scale Analysis, trend identification, Statistical technique application, data sample processing sample processing, and ICT Data formatting for reporting and analysis are just a few of the tasks performed by Data Analysts.
Data Analysis is done using programming languages like Excel, Python, R, Scala (for Data Science), and/or SDL/SQL. Tableau, C++, or Java. These are the most important and powerful tools that are commonly used to create spreadsheets for keeping track of and conducting financial research.
Businesses across a wide range of industries, including technology, telecommunications, insurance, advertising, financial services, healthcare, and are making significant investments in big data and setting up analytics departments, indicating the potential of data analytics. Future expansion is anticipated because sectors such as businesses, governments, and education – which have been sluggish to adopt big data analytics – have committed to using the technology more regularly in the future.
The course will cover working with NumPy and Pandas, handling data frames in Pandas, using variables, conditionals, loops, and functions in Python scripts, as well as handling machine learning using Scikit-Learn.
Top 10 Data Analytics Courses In Greece With Placements
1. IIM SKILLS
With the help of IIM SKILLS, a renowned Data Analytics Course in Greece, uncover your unrealized learning potential and set out on a life-changing path in the field of Data Analytics.
With the demands of the industry in mind, IIM SKILLS has created a comprehensive Data Analytics Course in Greece that gives students the tools they need to finish the modules.
The main goal is to provide students with a competitive edge in their job hunt by improving their industry-relevant skills. Students who complete the course will have acquired critical skills, such as a thorough comprehension of Excel’s command for Python concepts, which include Lists, Sets, Additions, Branches, Dictionaries, Objects, and Classes. These concepts are analogous to Python’s SQL command and query tool.
– Building SSIS packages for Integration and Project creation
Module 4: Introduction to Power BI
– Preparing Data and Modeling
– Data Analysis Expressions (DAX)
– Development of Reports (Power BI Visuals)
Module 5: Python-Based Data Analytics
– Overview of Fundamentals Statistics
– An Overview of the Fundamental Statistics
– Foundations of Mathematics – Overview
– Overview of Data Science and Analytics
– Core Python Essentials
– NumPy (Numerical Python) operations
– Overview of Pandas
– Python Data Cleaning
– Python Data Analysis
– Python Data Visualization
– Statistical Techniques and Hypothesis Testing
Module 6: Introduction to Tableau
– Data Management and Summaries
– Report Development (Tableau Visuals)
Module 7: Using R with Databases for Data Science
– Importing and Exporting Data
– Data Manipulation and Data Analysis
– R-Based Data Visualization
– Overview of Statistics
– Regression Problem Solving with Linear Regression
Module 8: Alteryx
– An outline of the Alteryx course and its core ideas
– Changing the Data Type and Renaming Fields with the Select Tool
– Comprehending Alteryx Settings and the User Environment
– Data Processing and Data Filtering
– Combining and blending data from several sources
– Data Purification Dispute Values
– Random sample
List of other Professional Courses from IIM SKILLS
The American College of Greece offers an MS in Data Science program is a state-of-the-art program that provides advanced knowledge and practical skills in significant data science. The American College of Greece is an outstanding Data Analytics course in Greece.
Students will get the chance to obtain a degree in Business Intelligence and Data Mining at SAS and learn how to turn real-world data into insights, solutions, and tools that support organizational decision-making.
A highly decorative degree program, the Master of Science in Data Analytics prepares students for careers as Information Technologists, particularly in processing large amounts of data, finding patterns in data, generating predictions, and efficiently visualizing and communicating data to support organizational decision-making.
The primary focus of this Data Analytics course in Greece is on fostering learners’ proficiency in handling diverse forms of data, such as textual, visual, and business transaction data.
The curriculum gives participants a well-balanced, theoretically grounded, and practically applied synthesis of the core concept knowledge and skill sets needed for Applied Mathematicians, Computer Scientists, Statisticians, and Business.
It also gives learners the option to pursue a professional pathway that is appropriate for immediate professional application or a researcher pathway that is appropriate for advanced undergraduate study and research.
The requirement for students is to finish 12 graduate courses or 36 US credits. A professional route that leads to an SOS professional certificate and project work with an organization is available to students, or they can choose the Researchers track, which is best, suited for in-depth postgraduate studies at Universities or employment in Research Departments of sizable corporations.
Qualifiable Conditions
The programs are excellent for recent college graduates who want to work as IT Professionals or as Engineers, Scientists, Economists, or Information Technologists.
Students with degrees in other fields, like Business or Social Science, are also eligible to apply.
The Fundamental Curriculum of Greece’s Data Analytics Training Programs
– Overview of Big Data
– Investigate and Examine Data
– Utilize Machine Learning
– Data Visualizations & Interaction
– Web Semantic
– Big Data in Business
– Store and Retrieving Data
– Search Engines and Web Mining
– Data Science in Machine Vision
– Natural Language Processing
– Career Path
– SAS Platform for Business Analytics
– Capstone Projects
– Researcher Pathway
– Competencies at the Program Level
– Advanced Machine Learning
What Should Students Expect Following Successful Program Completion?
– Assessments of the methods for handling and storing large amounts of Data.
– Business Data Transactions to applications using particular techniques.
– Examined the fundamental tools and techniques of machine learning to apply the appropriate methodology.
– Addressing commercial challenges with Data Science techniques.
– Records, Concepts, and disputes and effectively conveys them in a corporate setting.
Epsilon Data Analytics Institute in Greece is to introduce students to the theory and methods utilized in contemporary Data Analysis systems in a commercial context. The Data Analytics courses in Greece deepen the job of the Data Analyst and provide insight into how Data Analytics.
The Epsilon curriculum includes an exploration of the data ecosystem, as well as a range of on-premise and Cloud tool technologies and the emergence of big data platforms like Hadoop, Hive, and Spark.
Professionals with a wealth of industry expertise teach the program, which consists of topic-specific lectures delivered in an immersive style that blends important tool principles with real-world applications in Lab sessions and Live demos.
The University of Northampton has endorsed the Data Analytics degree program.
The Program’s Content
– Business Intelligence
– The Process of Data Analytics
– The Data Structure and Ecosystem
– ETL – The Data Ecosystem
– Big Data – The Data Ecosystem
– Data Mining and Warehousing
– Data Visualization
The Main Learning from the Course
– Free access to Online Bank and Epsilon Net subscription services is being provided to all students.
– All Epsilon materials are freely available and used.
– Fully assisting students and alumni in realizing their professional goals after graduation.
4. Bolton University
Offering an M.Sc degree program in Data Analytics and Technology, Bolton University is a top Data Analytics Institute in Greece. It’s a great option for anyone who wants to advance their Data Analytics knowledge and find a stable job in this emerging Business and Science sector.
Students will learn the foundational concepts of Data Analytics classes, enabling them to make use of the most important instruments and techniques available.
The top UK universities, industry leaders, and academics with a wealth of experience in Data Analysis work together to provide Master’s in Data Analytics courses in Greece. In addition, students will have the chance to work together with experts and other students from different fields, build networks, and establish global forms of cooperation that will benefit them in their future jobs.
Large-scale Data Analysis and Interpretation, Machine Learning, pattern and trend detection in commercial Data Processing and Management, and analysis of diverse data kinds like Text, Photos, Social media, etc, are among the main subjects covered.
Since Data Analytics is one of the fields with the quickest rate of growth right now, students who complete the program will have the possibility to work in a variety of businesses.
The Student Program’s Core Module
– Data Science
– Massive Data Technologies
– Research Methods
– Master Project
– Plotting solutions and scheduling ethical applications
Duration:
Regular programs last 12 weeks plus an additional 6 weeks for thesis preparation, whereas intermediate courses last 24 weeks plus 6 weeks for thesis preparation.
Qualification:
A basic graduation Honor degree in Computer Science, Software Engineering, Business, Management, or any related field.
IELTS 6.0 or equivalent.
Students’ expectations from Bolton University? – Combine technical expertise with administrative and planning skills
– Portions completed with strong, realistic content
– Flexible program beneficial for students who are working
– Educators with excellent contextual knowledge and expert practice.
5. College of Aristotle in Thessaloniki
The main goal of Aristotle College of Thessaloniki, a top Data Analytics institute in Greece, is to provide effective data management solutions that are necessary to support the rapid advancement of Web Technology.
The M.Sc. degree in Data and Web Knowledge at the university provides valuable insights into the retrieving, indexing, utilizing, and organizing information from massive data sets through a variety of scientific techniques and programming tools.
One of the program’s primary advantages is that its design and visual effects were developed with SAS assistance.
Program Module
1st Semester
Machine Learning, Technologies for Big Data Analytics, Distributed Data Management, Text Mining, and Natural Language Processing, Analysis of Social Networks.
The Aegean College IT School in collaboration with the University of Essex offers an Advanced Undergraduate Computing program initiating the BSc (Hons) Data Analysis courses in Greece. Being a part of Oracle Academy allows Aegean College students to access a vast library and earn labour credits.
The expansive, new program is in keeping with the latest developments in the PC lab industry. This particular stream is a top-notch academic program in the emerging sector of personal computers, tailored to meet the demands of Greek and international outlets.
Students begin the learning cycle by going through the main components that are common to all flows. Students will pack stream components, such as travel apps and PC-human interaction, in the second and third years.
The three-year academic program known as the Foundation Course at Data Analysis College in Greece equips students with all the knowledge and abilities required to monitor databases.
The well-written sections cover a broad range of computing concepts, with a focus on creating and building data. In addition, students learn about object-making software, cyber safety, and PC system architecture.
Timing of Course: 3 years
Greek is the language of instruction
Demand for Entry: High school diploma or IB
Level of Respect: ATEEN
Module of the Data Analytics courses in Greece:
– The Program’s Introduction
– System Creation and Analysis.
– Digital systems, as well as PC Core Module.
– Developing Application
– Introduction to Web-Based Development
– Database Production.
– Web-Based Program
– Computer Networks and Storage
– Data Science
– Data science with Python.
– Data Sciences and Massive Data.
7. Piraeus University
The Cyber Security and Information Science program at the University of Piraeus, a top Data Analytics Institute in Greece, is intended for IT and Computer Science professionals who want to enroll in a graduate program in computer science and learn about the most recent developments in Data and Business Analytics, infrastructure security, and Computer Science.
These areas are powerful, have rapid scientific advancement, and are in constant demand throughout Europe. For full-time students, the master’s Data Analytics Courses in Greece last three semesters, whereas for part-time students, they last six semesters.
To fulfil their requirements, the Business and Data Analytics track offers a wide variety of advanced courses. Students must finish multiple courses worth thirty credits in a semester.
The first semester has seven courses, whereas the second semester comprises six courses. For a maximum of thirty ECTS every semester, students may choose one or two elective subjects from other chapters to take as discretionary subjects. Under the guidance of one of the track supervisors, the third semester is devoted to writing a thesis on the newest subject in information science.
The following three options are available for the program to provide a Master of Science (MSc) in Information Science and Cybersecurity.
– Security of Information and Communication Systems (ICSS)
– Security and Reliability of Embedded Systems (ESSR)
– Analytics for Business and Data (BDA)
Time Frame: 1.5 years of full-time.
Commencement Date: Mid-October
Cost: 4,500 Euros
Greece’s Data Analytics Training Program’s Curriculum for Machine Learning and Data Analytics
CDS110: Management of Large Data
CDS111: Business Analytics Computational Tools
CDS112: Complexities and Algorithms
CDS115: Depth Learning
2nd Semester
CDS207: Business Analytics Using Mathematics Techniques
CDS208: Depth Learning (with Cybersecurity and Analytics Applications)
CDS209: Analytics and Management of Geospatial Data
CDS210: Analytical Visual
CDS213: Graph and Network Analytics
CDS214: Forecasting and Time-Series Analytics
The International Hellenic University’s School of Science & Technology department offers MSc in Data Analytics Courses in Greece.
The program is intended for professionals and recent graduates who want to expand their knowledge in the field of computing by offering higher education with a multidisciplinary approach to the operation, visualization, and processing of big data as well as related topics of computing techniques and technologies.
For full-time students, the Master’s program in Data Science consists of two semesters and a year of Master’s degree preparation; for part-time students, the program consists of four semesters. Every course is instructed in English.
Graduate students who participate in all relevant activities must acquire ninety European credits to complete the master’s degree.
Qualification:
Standards Science, Technology, Engineering, and Mathematics degrees are seen to work well with the curriculum. However, if you have a strong foundation in mathematics and statistics, a solid grasp of databases, and a fundamental understanding of programming, additional degrees will be taken into consideration.
Core Module of the Data Analytics Courses in Greece
– Advanced Database Systems
– Coursework Data Science for Theory and Application in Business
– Concepts and Principles of Machine Learning
– Programming for Data Science
– Statistical Techniques for Data Science
– Time Series Forecasting
– Big Data and Cloud Computing
– Consulting Project
– Exploratory Data Analysis and Visualization
– Advanced Machine Learning Data Mining Text Analysis and Natural Language Processing
– Elective Multimedia Data Analysis
– Information Retrieval
– Knowledge Management in the Web
– Social media and managing online communities
The program costs 3,700 Euros.
9. Kapodistrian University of Athens
Doctorate Students from other Greek and International Universities, seasoned professionals in the industry, and Professors and Researchers from the aforementioned Departments who have expertise in the program’s study areas are all teaching NKUA Data Analytics Courses in Greece.
The Data and Information Technologies Master Program is intensively interdisciplinary. The program concentrates on strengthening students’ skills, focusing mainly on Data Science, Large Databases, Math, Statistical Methods, Artificial Intelligence, and their applications in Life Science, Computational Biology, Biomedical Informatics, and Bioinformatics in advance.
The program’s focus is on topics related to the operations, processing, analysis, and software development of large or complex data. Experts will teach students the principles of mathematical models, algorithms, statistical analysis, image analysis, computational and structural biology, bioinformatics, and systems biology to improve human health.
Graduates from this program possess several fundamental skills that will allow them to pursue postdoctoral research, usually leading to a PhD, work in a variety of Industrial Laboratories and Organizations, or even launch their Businesses in participation and related fields.
10. University of Derby
The MSc Big Data Analytics courses in Greece are carefully designed to give students practical skills in a variety of Big Data Analytics-related subjects in addition to theoretical foundational principles.
The program’s primary goals are to mine, analyze, exploit, and manage information from big data utilizing a variety of software tools and scientific approaches.
The main features of the programs are their learning objectives and structures, which were created in conjunction with SAS and are taught by knowledgeable University of Derby faculty members.
The STEM or Business graduates who want to pursue a background in Big Data Analytics as well as Data Analytics professionals who want to advance their knowledge and abilities in this specialized field are the target audience for the Data Analytics Training program in Greece. As a result, this exceptionally unique degree offers fantastic career options in both academics and business.
The curriculum consists of six 20-credit modules and a 60-credit thesis that can be completed part-time over two years. The learning objectives and program frameworks, which were created using SAS Analytics, are the most important features. A complete project in the field of your choice connected the entire program through an individual scholarship module.
The Program Module For Data Analytics courses in Greece
– Overview of Data Analytics
– Principles, Process, and Pre-Process
– Typical techniques for Machine Learning
– Depth Learning and Neural Networks
– Sophisticated Clustering Methods
– DBSCAN and OPTICS
– Uses for Text, Audio, and Video Data Mining
– Lab time using R and Python
– Mathematical modeling and optimization – Overview
– Limited optimization Data hulls that are convex and nonconvex
– Frontier Analysis and Data envelopment analysis models and applications are examples of Data analysis optimization techniques
– Using streaming data for Data envelopment analysis.”
FAQs
1. How popular are Data Analytics Courses in Greece?
Indeed, a great deal of data is generated via online operations in the modern world, where digitalization has replaced all manual activities. Data analysts are critically needed to process and evaluate data to handle the nation’s enormous amount of data.
2. Do we need to know coding to be eligible for data analytics courses in Greece?
No, coding is not required for the Greece Data Analytics courses. All you need to know are the fundamentals of statistics and Excel.
3. What is the minimum salary a data analyst may expect after completing Data Analytics Courses in Greece?
The most recent data indicates the average minimum wage in Greece for a data analyst is 48.200 Euros.
Conclusion
The field of data analytics is expanding and is now well-liked by both professionals and students. One needs to develop the necessary abilities to outperform the competition and succeed before others to fill the selection and take advantage of these challenging work chances. However, you can change the trajectory of your career and improve your professional profile by enrolling in any reputable Data Analytics courses in Greece and earning a certification as a data analyst.
