DATA ANALYST CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYST LEAD MENTORS

DATA ANALYST COURSE FEE IN HUNGARY

Live Virtual

Instructor Led Live Online

HUF 430,430
HUF 244,256

  • IABAC® Certification
  • 6-Month | 200+ Learning Hours
  • 20 HOURS LEARNING A WEEK
  • 10 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Blended Learning

Self Learning + Live Mentoring

HUF 215,220
HUF 139,983

  • Self Learning + Live Mentoring
  • IABAC® Certification
  • 1 Year Access To Elearning
  • 10 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Learner assistance and support

Corporate Training

Customize Your Training


  • Instructor-Led & Self-Paced training
  • Customized Learning Options
  • Industry Expert Trainers
  • Case Study Approach
  • Enterprise Grade Learning
  • 24*7 Cloud Lab

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UPCOMING DATA ANALYST ONLINE CLASSES IN HUNGARY

BEST DATA ANALYTICS CERTIFICATIONS

The entire training includes real-world projects and highly valuable case studies.

IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.

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WHY DATAMITES INSTITUTE FOR DATA ANALYST COURSE

Why DataMites Infographic

SYLLABUS OF DATA ANALYST COURSE IN HUNGARY

MODULE 1: DATA ANALYSIS FOUNDATION

• Data Analysis Introduction
• Data Preparation for Analysis
• Common Data Problems
• Various Tools for Data Analysis
• Evolution of Analytics domain

MODULE 2: CLASSIFICATION OF ANALYTICS

• Four types of the Analytics
• Descriptive Analytics
• Diagnostics Analytics
• Predictive Analytics
• Prescriptive Analytics
• Human Input in Various type of Analytics

MODULE 3: CRIP-DM Model

• Introduction to CRIP-DM Model
• Business Understanding
• Data Understanding
• Data Preparation
Modeling, Evaluation, Deploying,Monitoring

MODULE 4: UNIVARIATE DATA ANALYSIS

• Summary statistics -Determines the value’s center and spread.
• Measure of Central Tendencies: Mean, Median and Mode
• Measures of Variability: Range, Interquartile range, Variance and Standard Deviation
• Frequency table -This shows how frequently various values occur.
• Charts -A visual representation of the distribution of values.

MODULE 5: DATA ANALYSIS WITH VISUAL CHARTS

• Line Chart
• Column/Bar Chart
• Waterfall Chart
• Tree Map Chart
• Box Plot

MODULE 6: BI-VARIATE DATA ANALYSIS

• Scatter Plots
• Regression Analysis
• Correlation Coefficients

MODULE 1: PYTHON BASICS

• Introduction of python
• Installation of Python and IDE
• Python Variables
• Python basic data types
• Number & Booleans, strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators

MODULE 2: PYTHON CONTROL STATEMENTS

• IF Conditional statement
• IF-ELSE
• NESTED IF
• Python Loops basics
• WHILE Statement
• FOR statements
• BREAK and CONTINUE statements

MODULE 3: PYTHON DATA STRUCTURES

• Basic data structure in python
• Basics of List
• List: Object, methods
• Tuple: Object, methods
• Sets: Object, methods
• Dictionary: Object, methods

MODULE 4: PYTHON FUNCTIONS

• Functions basics
• Function Parameter passing
• Lambda functions
• Map, reduce, filter functions

MODULE 1 : OVERVIEW OF STATISTICS 

  • Introduction to Statistics
  • Descriptive And Inferential Statistics
  • Basic Terms Of Statistics
  • Types Of Data

MODULE 2 : HARNESSING DATA 

  • Random Sampling
  • Sampling With Replacement And Without Replacement
  • Cochran's Minimum Sample Size
  • Types of Sampling
  • Simple Random Sampling
  • Stratified Random Sampling
  • Cluster Random Sampling
  • Systematic Random Sampling
  • Multi stage Sampling
  • Sampling Error
  • Methods Of Collecting Data

MODULE 3 : EXPLORATORY DATA ANALYSIS 

  • Exploratory Data Analysis Introduction
  • Measures Of Central Tendencies: Mean, Median And Mode
  • Measures Of Central Tendencies: Range, Variance And Standard Deviation
  • Data Distribution Plot: Histogram
  • Normal Distribution & Properties
  • Z Value / Standard Value
  • Empherical Rule  and Outliers
  • Central Limit Theorem
  • Normality Testing
  • Skewness & Kurtosis
  • Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance
  • Covariance & Correlation

MODULE 4 : HYPOTHESIS TESTING 

  • Hypothesis Testing Introduction
  • P- Value, Critical Region
  • Types of Hypothesis Testing
  • Hypothesis Testing Errors : Type I And Type Ii
  • Two Sample Independent T-test
  • Two Sample Relation T-test
  • One Way Anova Test
  • Application of Hypothesis testing

MODULE 1: COMPARISION AND CORRELATION ANALYSIS

• Data comparison Introduction,
• Performing Comparison Analysis on Data
• Concept of Correlation
• Calculating Correlation with Excel
• Comparison vs Correlation
• Hands-on case study : Comparison Analysis
• Hands-on case study Correlation Analysis

MODULE 2: VARIANCE AND FREQUENCY ANALYSIS

• Variance Analysis Introduction
• Data Preparation for Variance Analysis
• Performing Variance and Frequency Analysis
• Business use cases for Variance Analysis
• Business use cases for Frequency Analysis

MODULE 3: RANKING ANALYSIS

• Introduction to Ranking Analysis
• Data Preparation for Ranking Analysis
• Performing Ranking Analysis with Excel
• Insights for Ranking Analysis
• Hands-on Case Study: Ranking Analysis

MODULE 4: BREAK EVEN ANALYSIS

• Concept of Breakeven Analysis
• Make or Buy Decision with Break Even
• Preparing Data for Breakeven Analysis
• Hands-on Case Study: Manufacturing

MODULE 5: PARETO (80/20 RULE) ANALSYSIS

• Pareto rule Introduction
• Preparation Data for Pareto Analysis,
• Performing Pareto Analysis on Data
• Insights on Optimizing Operations with Pareto Analysis
• Hands-on case study: Pareto Analysis

MODULE 6: Time Series and Trend Analysis

• Introduction to Time Series Data
• Preparing data for Time Series Analysis
• Types of Trends
• Trend Analysis of the Data with Excel
• Insights from Trend Analysis

MODULE 7: DATA ANALYSIS BUSINESS REPORTING

• Management Information System Introduction
• Various Data Reporting formats
• Creating Data Analysis reports as per the requirements

MODULE 1: DATA ANALYTICS FOUNDATION

• Business Analytics Overview
• Application of Business Analytics
• Benefits of Business Analytics
• Challenges
• Data Sources
• Data Reliability and Validity

MODULE 2: OPTIMIZATION MODELS

• Predictive Analytics with Low Uncertainty;Case Study
• Mathematical Modeling and Decision Modeling
• Product Pricing with Prescriptive Modeling
• Assignment 1 : KERC Inc, Optimum Manufacturing Quantity

MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION

• Mathematics behind Linear Regression
• Case Study : Sales Promotion Decision with Regression Analysis
• Hands on Regression Modeling in Excel

MODULE 4: DECISION MODELING

• Predictive Analytics with High Uncertainty
• Case Study-Monte Carlo Simulation
• Comparing Decisions in Uncertain Settings
• Trees for Decision Modeling
• Case Study : Supplier Decision Modeling - Kickathlon Sports Retailer

MODULE 1: MACHINE LEARNING INTRODUCTION

• What Is ML? ML Vs AI
• ML Workflow, Popular ML Algorithms
• Clustering, Classification And Regression
• Supervised Vs Unsupervised

MODULE 2: ML ALGO: LINEAR REGRESSSION

• Introduction to Linear Regression
• How it works: Regression and Best Fit Line
• Hands-on Linear Regression with ML Tool

MODULE 3: ML ALGO: LOGISTIC REGRESSION

• Introduction to Logistic Regression;
• Classification & Sigmoid Curve
• Hands-on Logistics Regression with ML Tool

MODULE 4: ML ALGO: KNN

• Introduction to KNN; Nearest Neighbor
• Regression with KNN
• Hands-on: KNN with ML Tool

MODULE 5: ML ALGO: K MEANS CLUSTERING

• Understanding Clustering (Unsupervised)
• Introduction to KMeans and How it works
• Hands-on: K Means Clustering

MODULE 6: ML ALGO: DECISION TREE

• Decision Tree and How it works
• Hands-on: Decision Tree with ML Tool

MODULE 7: ML ALGO: SUPPORT VECTOR MACHINE (SVM)

• Introduction to SVM
• How It Works: SVM Concept, Kernel Trick
• Hands-on: SVM with ML Tool

MODULE 8: ARTIFICIAL NEURAL NETWORK (ANN)

• Introduction to ANN, How It Works
• Back propagation, Gradient Descent
• Hands-on: ANN with ML Tool

MODULE 1: DATABASE INTRODUCTION

• DATABASE Overview
• Key concepts of database management
• CRUD Operations
• Relational Database Management System
• RDBMS vs No-SQL (Document DB)

MODULE 2: SQL BASICS

• Introduction to Databases
• Introduction to SQL
• SQL Commands
• MY SQL workbench installation

MODULE 3: DATA TYPES AND CONSTRAINTS

• Numeric, Character, date time data type
• Primary key, Foreign key, Not null
• Unique, Check, default, Auto increment

MODULE 4: DATABASES AND TABLES (MySQL)

• Create database
• Delete database
• Show and use databases
• Create table, Rename table
• Delete table, Delete table records
• Create new table from existing data types
• Insert into, Update records
• Alter table

MODULE 5: SQL JOINS

• Inner join, Outer Join
• Left join, Right Join
• Self Join, Cross join
• Windows Functions: Over, Partition, Rank

MODULE 6: SQL COMMANDS AND CLAUSES

• Select, Select distinct
• Aliases, Where clause
• Relational operators, Logical
• Between, Order by, In
• Like, Limit, null/not null, group by
• Having, Sub queries

MODULE 7: DOCUMENT DB/NO-SQL DB

• Introduction of Document DB
• Document DB vs SQL DB
• Popular Document DBs
• MongoDB basics
• Data format and Key methods
• MongoDB data management

MODULE 1: BIG DATA INTRODUCTION

• Big Data Overview
• Five Vs of Big Data
• What is Big Data and Hadoop
• Introduction to Hadoop
• Components of Hadoop Ecosystem
• Big Data Analytics Introduction

MODULE 2: HDFS AND MAP REDUCE

• HDFS – Big Data Storage
• Distributed Processing with Map Reduce
• Mapping and reducing stages concepts
• Key Terms: Output Format, Partitioners, Combiners, Shuffle, and Sort

MODULE 3: PYSPARK FOUNDATION

• PySpark Introduction
• Spark Configuration
• Resilient distributed datasets (RDD)
• Working with RDDs in PySpark
• Aggregating Data with Pair RDDs

MODULE 4: SPARK SQL and HADOOP HIVE

• Introducing Spark SQL
• Spark SQL vs Hadoop Hive

MODULE 1: TABLEAU FUNDAMENTALS

• Introduction to Business Intelligence & Introduction to Tableau
• Interface Tour, Data visualization: Pie chart, Column chart, Bar chart.
• Bar chart, Tree Map, Line Chart
• Area chart, Combination Charts, Map
• Dashboards creation, Quick Filters
• Create Table Calculations
• Create Calculated Fields
• Create Custom Hierarchies

MODULE 2: POWER-BI BASICS

• Power BI Introduction
• Basics Visualizations
• Dashboard Creation
• Basic Data Cleaning
• Basic DAX FUNCTION

MODULE 3: DATA TRANSFORMATION TECHNIQUES

• Exploring Query Editor
• Data Cleansing and Manipulation:
• Creating Our Initial Project File
• Connecting to Our Data Source
• Editing Rows
• Changing Data Types
• Replacing Values

MODULE 4: CONNECTING TO VARIOUS DATA SOURCES

• Connecting to a CSV File
• Connecting to a Webpage
• Extracting Characters
• Splitting and Merging Columns
• Creating Conditional Columns
• Creating Columns from Examples
• Create Data Model

OFFERED DATA ANALYST COURSES IN HUNGARY

DATA ANALYST COURSE REVIEWS

ABOUT DATA ANALYST TRAINING IN HUNGARY

A Data Analyst course in Hungary offers comprehensive training in statistical analysis, data visualization, and programming, equipping students with the skills to interpret and present insights from large datasets. With a growing demand for data-driven decision-making in various industries, graduates can pursue rewarding careers in analytics, business intelligence, and research. The global big data analytics market achieved a notable valuation of 240 billion U.S. dollars in 2021, and forecasts suggest significant expansion, projecting a surpassing of 650 billion dollars by 2029, as reported by Statista.

The Data Analytics sector in Hungary is witnessing remarkable expansion, mirroring global patterns. The rising prevalence of digitization and heightened reliance on data-driven insights in diverse industries are driving the demand for proficient professionals capable of maximizing the potential of data.

DataMites, a globally acclaimed institution, is excited to present its comprehensive 6-month Certified Data Analyst Training Course in Hungary. Covering crucial topics such as No-code, MySQL, Power BI, Excel, and Tableau, the program offers a deep 200-hour immersive learning experience. What sets DataMites apart is its international accreditation from IABAC, ensuring participants receive a globally recognized certification. With a decade of expertise, DataMites has successfully guided over 50,000+ learners worldwide.

Alongside in-person training, the institute also offers online data analyst training in Hungary, providing valuable insights and internship opportunities to propel students' careers forward.

DataMites is excited to unveil a thoughtfully crafted Certified Data Analyst Training in Hungary, structured into three distinct phases:

Phase 1: Initial Self-Study

Embark on your educational journey with top-notch videos, employing an easily comprehensible learning approach.

Phase 2: 3-Month Duration

Engage in live training sessions, dedicating 20 hours per week to a comprehensive syllabus. Participate in hands-on projects under the guidance of seasoned trainers and mentors.

Phase 3: 3-Month Duration

Enhance your skills through project mentoring, completion of 10 capstone projects, participation in real-time internships, and contribution to a live client project. Obtain IABAC and data analytics internship certifications in Hungary, solidifying your expertise in the dynamic field of Data Analytics.

DataMites is excited to present its certified data analyst course in Hungary, delivering a comprehensive learning experience enriched with several key features.

Led by Ashok Veda and Expert Faculty: Headed by Ashok Veda, Founder & CEO of Rubixe™, a seasoned professional with over 19 years of experience in Data Analytics, DataMites guarantees top-notch education. Under Ashok Veda's guidance, the program integrates the latest insights from Data Analytics and AI, providing students with invaluable knowledge.

Course Highlights - Mastering Data Analytics: Embark on a six-month learning journey with our no-code program (optional Python), dedicating 20 hours per week for over 200 learning hours. Attain global recognition with the esteemed IABAC® Certification, validating your proficiency in data analytics.

Flexible Learning - Tailored to Your Schedule: Personalize your learning experience with our flexible online data analytics courses in Hungary and self-study options. This flexibility allows you to balance professional commitments while excelling in data analytics.

Hands-On Experience - Projects and Internships: Apply your skills to real-world scenarios through 10 capstone projects and a live client project. Our structured data analyst courses with internships in Hungary provide valuable industry experience, enhancing your practical expertise in data analytics.

Career Assistance and Networking: Beyond education, DataMites offers comprehensive job assistance, personalized resume crafting, data analytics interview preparation, and continuous updates on job opportunities. Connect with a network of industry professionals through our job references, positioning you for success in your Data Analytics Career.

DataMites Exclusive Learning Community: Become part of our vibrant and exclusive learning community. Engage with peers, share insights, and collaborate in an environment fostering continuous learning and growth.

Affordable Pricing and Scholarships: Access quality education with our affordable pricing structure for Data Analytics Course Fees in Hungary, ranging from HUF 1,50,385 to HUF 4,62,426. Explore scholarship opportunities to support your educational journey and join DataMites for a future enriched with data analytics expertise.

Hungary, nestled in Central Europe, boasts a rich cultural heritage with its historic architecture, thermal spas, and vibrant folk traditions. The country's diverse economy thrives on industries such as automotive manufacturing, information technology, and agriculture, contributing to its dynamic and resilient economic landscape.

The future of data analytics in Hungary appears promising, as the country increasingly embraces advanced technologies. With a growing demand for data-driven insights, Hungary is poised to see significant developments in data analytics, contributing to innovation across various industries. Additionally, the salary of a data analyst in Hungary ranges from HUF 6,274,331 per year according to the PayScale report.

Embark on a transformative learning experience by enrolling in the Certified Data Analyst course in Hungary at DataMites Institute. Our carefully crafted programs are designed to provide you with essential skills vital for success in the dynamic field of data analytics. Join DataMites today to establish yourself as a valuable contributor to the ongoing revolution in data analytics, offering a diverse range of courses including Data Science, MlOps, Machine Learning, Artificial Intelligence, Tableau, Deep Learning, Python, and Data Mining for comprehensive skill development.

ABOUT DATAMITES DATA ANALYST COURSE IN HUNGARY

Data analytics encompasses the interpretation and analysis of data to extract insights, facilitating well-informed decision-making.

A data analyst's responsibilities include interpreting data, generating reports, and conveying findings to aid organizations in making decisions based on data.

Critical skills for a data analytics career include proficiency in statistical analysis, data visualization, programming languages (such as Python or R), and adept database management.

Data analysts are tasked with collecting, processing, and analyzing data, creating comprehensive reports, and providing actionable insights to support strategic business decisions.

Data analytics opens up diverse opportunities across industries like finance, healthcare, marketing, and technology, showcasing its broad applicability.

Prominent roles include Data Analyst, Business Analyst, Data Scientist, and Machine Learning Engineer, each contributing uniquely to the dynamic landscape of data analytics.

The future of data analysis involves increased automation, integration of AI technologies, and a rising demand for skilled professionals capable of adapting to evolving analytical landscapes.

While specific requirements may vary, a common baseline for a data analyst course often involves attaining a bachelor's degree in a relevant field.

Essential tools for data analytics learning encompass Excel, SQL, programming languages like Python or R, and visualization tools such as Tableau, forming a foundational toolkit for comprehensive data analysis.

Embarking on the study of data analytics is both challenging and rewarding, demanding analytical thinking and a commitment to continuous learning to stay abreast of industry advancements.

A solid understanding of SQL is essential for data analysts to adeptly query and manipulate databases, ensuring efficient data analysis processes.

Achieving proficiency in data analytics within six months is feasible through focused learning and practical hands-on experience.

The expected fees for the Data Analyst Course in Hungary for 2024 are projected to range from HUF 100,000 to HUF 400,000.

Certified Data Analyst courses confer industry-recognized credentials, validating an individual's competence in the field of data analysis.

Internships play a crucial role in data analytics learning by providing invaluable real-world experience and exposing learners to industry practices, enhancing their practical skills.

Projects contribute to an enriched learning experience in data analytics by allowing the application of theoretical knowledge to practical scenarios, fostering hands-on experience and skill development.

Data analytics offers a broad career scope, encompassing opportunities in data engineering, business intelligence, and data science, providing diverse pathways for career growth.

While beneficial, Python is not always a prerequisite for data analysts; however, proficiency in at least one programming language is recommended for effective data analysis.

While coding is part of data analytics, the extent varies; proficiency in scripting languages can be advantageous, depending on the complexity of the analysis.

Data analytics is widely acknowledged as a challenging field due to its multidisciplinary nature, offering rewarding career opportunities for those who navigate its complexities successfully.

The salary of a data analyst in Hungary ranges from HUF 6,274,331 per year according to the PayScale report.

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FAQ’S OF DATA ANALYST TRAINING IN HUNGARY

DataMites stands out as a premier provider of data analyst certification training in Hungary, offering tangible evidence of proficiency in data analytics. The program equips participants with essential skills for data interpretation and decision-making, opening doors to lucrative opportunities with reputable multinational companies. A certification from DataMites not only demonstrates competence but also signifies the ability to fulfil specific job roles at professional standards, enhancing its value beyond a basic data analytics certificate.

The Certified Data Analyst Course in Hungary by DataMites is ideal for individuals aspiring to enter the fields of data analytics or data science. With no coding prerequisites, this course is accessible to all, making it a perfect choice for beginners. The well-structured training program ensures a comprehensive understanding of the subject, providing an excellent opportunity for those intrigued by analytics to delve deeper into the field.

The Data Analyst Course in Hungary by DataMites spans approximately 6 months, comprising 200+ hours of learning with a recommended commitment of 20 hours per week. This duration ensures an in-depth coverage of the course material.

The certified data analyst course in Hungary encompasses the following tools:

  • MySQL
  • Anaconda
  • MongoDB
  • Hadoop
  • Apache PySpark
  • Tableau
  • Power BI
  • Google BERT
  • Tensor Flow
  • Advanced Excel
  • Numpy
  • Pandas
  • Google Colab
  • GitHub
  • Atlassian BitBucket 

Choosing DataMites for the Certified Data Analyst Course in Hungary ensures an exceptional learning experience. With a flexible study environment, a curriculum tailored for real-world applications, distinguished instructors, and an exclusive practice lab, participants thrive within a robust learning community. The program provides lifetime access, fostering continuous growth through unlimited hands-on projects. With dedicated placement support, DataMites positions itself as a comprehensive and advantageous option for those aspiring to become data analysts.

The Data Analytics course fees in Hungary offered by DataMites range from HUF 1,50,385 to HUF 4,62,426.

The Certified Data Analyst Course in Hungary covers a broad range of topics, including Data Analysis Foundation, Statistics Essentials, Data Analysis Associate, Advanced Data Analytics, Predictive Analytics with Machine Learning, Database: SQL and MongoDB, Version Control with Git, Big Data Foundation, Python Foundation, culminating in the Certified Business Intelligence (BI) Analyst module. This meticulously designed curriculum ensures a comprehensive understanding of essential concepts for a successful data analytics career.

Certainly, DataMites in Hungary provides substantial one-on-one support from instructors to enhance participants' comprehension of data analytics course content, creating an optimal learning environment.

In Hungary, DataMites accepts various payment methods, including cash, debit cards, credit cards (Visa, Mastercard, American Express), checks, EMI, PayPal, and net banking. This flexibility offers convenient options for participants to facilitate their course enrollment and payment procedures.

The Certified Data Analyst Course in Hungary at DataMites is led by Ashok Veda, a highly esteemed Data Science coach and AI expert. The team includes elite mentors and faculty members with hands-on experience from prestigious companies and renowned institutes like IIMs, ensuring exceptional mentorship and guidance throughout participants' learning journeys.

The Flexi Pass in DataMites' Data Analytics Course in Hungary allows participants to select batches that align with their schedules, offering enhanced flexibility in training. This adaptable option enables learners to customize the course according to their availability, providing increased convenience and accessibility.

Certainly, upon successfully completing DataMites' Certified Data Analyst Course in Hungary, participants receive the prestigious IABAC Certification. This widely recognized certification validates their proficiency in data analytics, bolstering their credibility within the industry.

DataMites follows a results-driven approach in its Certified Data Analyst Course in Hungary, integrating hands-on practical sessions, real-world case studies, and industry-relevant projects. This immersive methodology ensures participants not only grasp theoretical concepts but also acquire practical skills, effectively preparing them for the dynamic field of data analytics.

DataMites provides flexibility with options like Online Data Analytics Training in Hungary or Self-Paced Training. Participants can choose the mode that suits their learning preferences and schedule, whether through instructor-led online sessions or self-paced learning. Both approaches offer a comprehensive and accessible educational experience tailored to individual needs.

In the event of a missed data analytics session in Hungary, DataMites provides recorded sessions, enabling individuals to catch up on the missed content at their convenience. This flexibility supports continuous learning and mitigates the impact of occasional absence.

To attend DataMites' data analytics training in Hungary, participants need to bring a valid photo ID, such as a national ID card or driver's license. This documentation is essential for obtaining the participation certificate and scheduling any relevant certification exams.

In Hungary, DataMites organizes personalized data analytics career mentoring sessions, where experienced mentors offer guidance on industry trends, resume building, and interview preparation. These interactive sessions focus on individual career goals, providing customized advice to navigate the dynamic landscape of data analytics successfully.

The Certified Data Analyst Course in Hungary offered by DataMites holds significant value as the most comprehensive non-coding course available, catering to individuals from non-technical backgrounds. The program offers a unique combination of a 3-month internship in an AI company, an experience certificate, and training by expert faculty, ultimately leading to the prestigious IABAC Certification.

Certainly, DataMites in Hungary provides an internship alongside the Certified Data Analyst Course through exclusive collaborations with prominent Data Science companies. This exceptional opportunity allows learners to apply their acquired knowledge in creating real-world data models, benefiting businesses, with expert guidance from DataMites ensuring a meaningful and practical internship experience.

DataMites in Hungary integrates live projects into the data analyst course, featuring 5+ Capstone Projects and 1 Client/Live Project. This hands-on experience enables participants to apply their skills in real-world scenarios, enhancing practical proficiency and industry readiness.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

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