DATA ANALYST CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYST LEAD MENTORS

DATA ANALYST COURSE FEE IN TURKEY

Live Virtual

Instructor Led Live Online

TRY 51,560
TRY 29,263

  • 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

TRY 25,780
TRY 16,768

  • 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

ARE YOU LOOKING TO UPSKILL YOUR TEAM ?

Enquire Now

UPCOMING DATA ANALYST ONLINE CLASSES IN TURKEY

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.

images not display images not display

WHY DATAMITES INSTITUTE FOR DATA ANALYST COURSE

Why DataMites Infographic

SYLLABUS OF DATA ANALYST COURSE IN TURKEY

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 TURKEY

DATA ANALYST COURSE REVIEWS

ABOUT DATA ANALYST TRAINING IN TURKEY

Embark on a journey into the captivating world of Data Analytics, a domain that plays a pivotal role in shaping the future. Globally, the Data Analytics Market soared to USD 31,345.89 million in 2022, with a projected Compound Annual Growth Rate (CAGR) of 24.17% through the forecast period, reaching a remarkable USD 114,877.14 million by 2028.

In Turkey, the Data Analytics Industry is experiencing significant growth, mirroring global trends. The increasing reliance on data-driven decision-making across sectors has elevated the demand for skilled professionals proficient in navigating the intricacies of data analysis.

Enter the realm of Data Analytics with DataMites, a globally recognized institute dedicated to empowering individuals in Turkey. As a leading training institute, we offer a Certified Data Analyst Course in Turkey tailored for beginners and intermediate learners in the field. This career-oriented data analyst program in Turkey is meticulously designed to provide a robust foundation in Data Analysis, covering essential aspects such as Data Science Foundation, Statistics, Visual Analytics, Data Modeling, and Predictive Modeling.

Our program at DataMites goes beyond education; it is a stepping stone to a successful career. As a testament to the quality of our training, the certified data analyst training in Turkey includes IABAC Certification, a globally recognized credential that enhances your credibility in the competitive landscape of Data Analytics.

Structured Learning Journey at DataMites:

DataMites offers a comprehensive data analytics courses in Turkey in three phases, ensuring a well-rounded learning experience for individuals in Turkey.

Phase 1: Pre-Course Self-Study

Begin with a preparatory phase involving pre-course self-study. Access high-quality videos employing an easy learning approach, setting the foundation for subsequent modules.

Phase 2: 3-Month Live Training

Dive into an intensive 3-month live training phase, committing 20 hours a week. Benefit from a comprehensive syllabus, hands-on projects, and guidance from expert trainers and mentors.

Phase 3: 3-Month Project Mentoring

Conclude with a 3-month project mentoring phase, engaging in 5+ capstone projects. This phase includes a real-time data analyst internship in Turkey and a client/live project, culminating in IABAC and Internship Certifications.

Certified Data Analyst Courses in Turkey - Choosing DataMites 

Expert-Led Learning with Ashok Veda:

At DataMites, education is guided by industry excellence, with Ashok Veda at the helm, boasting over 19 years of experience in Data Analytics and AI. As the Founder & CEO at Rubixe™, his leadership ensures top-tier education, enriching your learning journey.

Innovative Course Curriculum:

Our program features a No-Code Program with an optional Python track, offering a comprehensive 6-month learning experience. Dedicate 20 hours per week, accumulating 200+ learning hours.

Global Certification and Flexible Learning:

Achieve industry recognition with IABAC® Certification. Our flexible learning approach allows you to seamlessly blend online data analytics courses in Turkey with self-study options, accommodating your schedule.

Practical Projects and Internship Opportunities:

Immerse yourself in real-world applications with 5+ capstone projects and a client/live project. The program also includes a valuable internship opportunity for hands-on experience.

Comprehensive Career Support:

Benefit from end-to-end job support, personalized resume and data analytics interview preparation, job updates, and valuable connections. Join DataMites' exclusive learning community for continuous growth.

Affordable Pricing and Scholarships:

Make quality education accessible with our affordable pricing. Data Analytics Training Fees in Turkey range from TRY 12,884 to TRY 39,618. Explore scholarship opportunities to further enhance your learning journey.

The Data Analytics Industry in Turkey is undergoing a transformative phase, driven by the increasing integration of data-driven strategies across various sectors. As the nation embraces digital transformation, the demand for skilled professionals in Data Analytics is on the rise, creating a dynamic and evolving landscape for career opportunities.

In Turkey, Data Analysts command a lucrative position in the job market, reflecting their pivotal role in deciphering complex datasets for actionable insights. According to Payscale, the average annual salary for a Data Analyst in Turkey stands at an impressive 83,700 TRY. As businesses increasingly rely on data-driven approaches, the demand for skilled Data Analysts in Turkey continues to grow, solidifying their status as highly paid professionals in the industry.

Embark on a transformative journey with DataMites, your gateway to excellence in Data Analytics. As the premier institute, we offer a Certified Data Analyst Course Training in Turkey, guided by industry expert Ashok Veda, ensuring a robust foundation and recognized credentials through IABAC Certification.

DataMites goes beyond Data Analytics, offering courses in Artificial Intelligence, Machine Learning, Python, Data Engineering, Tableau, Data Science, and more. Our comprehensive approach prepares you for the dynamic landscape of the technology industry, enhancing your career prospects.

ABOUT DATAMITES DATA ANALYST COURSE IN TURKEY

Data analytics involves the systematic examination of raw data to derive meaningful insights, patterns, and trends. Employing statistical and computational techniques, it transforms data into valuable information for informed decision-making across various industries.

Essential skills encompass proficiency in programming languages (e.g., Python or R), statistical analysis, data visualization, database management, and critical thinking. Effective communication is vital for conveying insights to non-technical stakeholders.

Key roles include Data Analyst, Business Intelligence Analyst, Data Scientist, Database Administrator, and Machine Learning Engineer. Each position contributes to leveraging data for organizational decision-making in distinct ways.

Practical applications of data analytics include fraud detection in finance, personalized marketing in e-commerce, predictive maintenance in manufacturing, healthcare data analysis for better patient outcomes, and optimizing supply chain logistics through data-driven insights.

To become a Data Analyst, acquire relevant education (often a bachelor's degree), develop proficiency in data analysis tools and programming languages, gain practical experience through internships or projects, and continuously update skills to stay abreast of industry trends.

The future of data analysis is promising, driven by advancements in artificial intelligence, machine learning, and big data technologies. Increasing reliance on data-driven decision-making across industries is expected to create abundant opportunities for skilled professionals.

To embark on a successful journey in data analytics, mastering key tools is essential. Proficiency in Python or R for programming opens avenues for data manipulation, while SQL expertise is crucial for effective database management. Additionally, familiarity with data visualization tools like Tableau or Power BI enhances the presentation of insights, making the learning process comprehensive and hands-on.

The field of data analytics poses a multifaceted challenge, demanding expertise in statistics, programming, and a nuanced understanding of business dynamics. Navigating through diverse datasets to extract meaningful insights requires a robust skill set, making the course both intellectually stimulating and rewarding.

Typically, a bachelor's degree in a related field such as statistics, mathematics, computer science, or business is the minimum qualification. Some courses may consider candidates with relevant work experience or equivalent certifications.

In the realm of cybersecurity, data analytics serves as a linchpin for identifying and thwarting threats. Analyzing vast datasets enables the detection of anomalies and patterns, empowering cybersecurity professionals to stay ahead of potential breaches and fortify digital defenses.

Data analytics transforms education by providing valuable insights into student performance, learning patterns, and predictive outcomes. Educators leverage this information to tailor learning experiences, enhance engagement, and optimize teaching methodologies, fostering a more effective and personalized educational landscape.

While achieving complete mastery in data analytics within six months is an ambitious goal, focused dedication, hands-on projects, and targeted learning can lead to a solid foundation and practical skills. The time frame, though, depends on individual commitment and prior knowledge.

Begin your data analytics journey by enrolling in reputable courses or pursuing degrees in the field. Online platforms offer comprehensive programs. Engage in practical projects, collaborate with online communities, and stay updated on industry trends to solidify your skills. Continuous learning and hands-on experience are key to mastering data analytics.

Internships are pivotal in bridging the gap between theoretical knowledge and practical application in data analytics. Real-world projects offer hands-on experience, honing skills, and providing exposure to industry dynamics. This immersion is essential for developing problem-solving capabilities, teamwork, and a holistic understanding of analytics in a professional setting.

Yes, data analytics often involves coding, with Python and R being widely used languages. Proficiency in coding is beneficial for tasks like data cleaning, statistical analysis, and algorithm creation. While extensive coding may vary depending on the role, having a solid coding foundation enhances your capabilities in handling and analyzing data effectively.

In Turkey, a Data Analyst commands an impressive average annual salary of 83,700 TRY, as reported by Payscale. This competitive compensation reflects the growing demand for skilled professionals in the field, emphasizing the pivotal role data analysts play in transforming raw data into actionable insights. 

Artificial Intelligence (AI) and data analytics are interconnected fields. AI relies on data analytics to make informed decisions, while data analytics leverages AI algorithms for advanced pattern recognition. Together, they amplify the capabilities of predictive modeling, enhancing efficiency and accuracy in extracting insights from vast datasets.

Social media platforms leverage data analytics extensively for user engagement, content optimization, and targeted advertising. Analyzing user behavior, sentiment analysis, and tracking trends empower businesses to tailor their strategies. Data analytics ensures personalized user experiences, content relevance, and effective marketing campaigns across various social media channels.

  • Discuss a challenging data analysis project you've worked on.
  • How do you handle missing or incomplete data in your analysis?
  • Explain the significance of A/B testing in data analytics.
  • What data visualization tools are you proficient in, and why?
  • Elaborate on a situation where you made a significant impact through your data analysis skills.
  • How do you communicate complex analytical findings to non-technical stakeholders?
  • Discuss your approach to handling and securing sensitive data in your analytics projects.
  • Explain the steps you take to ensure the quality and accuracy of your data before analysis.

DataMites is a renowned institute offering high-quality data analytics courses in Turkey. Their programs encompass a holistic curriculum, hands-on projects, and industry-relevant training. The emphasis on practical skills, expert faculty, and recognition within the industry make DataMites a preferred choice for aspiring data analysts.

View more

FAQ’S OF DATA ANALYST TRAINING IN TURKEY

Opt for DataMites' Certified Data Analyst Course in Turkey for its flexible learning, job-focused curriculum, elite instructors, exclusive practice lab access, vibrant learning community, and lifetime course access. With unlimited projects and placement assistance, it's an all-encompassing program for aspiring data analysts.

DataMites' Data Analyst Course in Turkey is a 6-month program with an engaging structure. Participants can expect 20 hours of learning per week, accumulating to over 200 learning hours, ensuring a comprehensive and immersive educational experience.

DataMites' certified data analyst training in Turkey covers a range of essential tools, including Advanced Excel, MySQL, MongoDB, Git, GitHub, Atlassian BitBucket, Hadoop, Apache Pyspark, Anaconda, Google Collab, Numpy, Pandas, Tableau, Power BI. This comprehensive toolkit ensures participants are well-equipped for diverse data analytics challenges.

DataMites' Certified Data Analyst Course in Turkey stands out with its specialized focus on advanced analytics and business insights. It is a NO-CODE program, allowing data analytics and managers to delve into advanced analytics without a programming background. The course is continually updated to align with industry needs, ensuring a structured and efficient learning experience.

The Certified Data Analyst Course by DataMites in Turkey is ideal for beginners and intermediate learners in the data analytics field. It's a career-oriented program providing a robust foundation in data analysis, data science, statistics, visual analytics, data modeling, and predictive modeling.

DataMites' Data Analytics Course in Turkey is priced between TRY 12,884 and TRY 39,618. This flexible fee structure caters to diverse budgets, ensuring accessibility to a comprehensive data analytics program designed to enhance career prospects in the field.

The Certified Data Analyst Course in Turkey encompasses a comprehensive curriculum, 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, and concludes with Certified Business Intelligence (BI) Analyst training for a well-rounded skill set.

For the Certified Data Analytics Course at DataMites in Turkey, various payment methods are accepted, including cash, debit cards, checks, credit cards (Visa, Mastercard, American Express), EMI options, PayPal, and net banking. This flexibility ensures ease and convenience for participants in managing their course fees.

The Certified Data Analyst Course at DataMites in Turkey is led by Ashol Veda, a highly respected Data Science coach and AI expert, ensuring top-notch mentorship. The elite mentors and faculty members possess real-time experience from leading companies and renowned institutes like IIMs, guaranteeing quality education and industry-relevant insights.

The Flexi Pass for the Certified Data Analyst Course in Turkey at DataMites provides participants with the flexibility to choose a convenient schedule for their training. This adaptable option caters to diverse timelines, allowing learners to balance their professional commitments while pursuing the certification.

Yes, upon completing the Certified Data Analyst Course in Turkey at DataMites, aspirants will receive IABAC Certification. This globally recognized certification validates their proficiency in data analytics, enhancing career prospects in the field.

Yes, DataMites offers comprehensive support for understanding data analytics course topics in Turkey. Their expert guidance ensures clarity and proficiency in analytics concepts, providing valuable assistance throughout the learning journey.

DataMites employs a practical and hands-on learning methodology for the Certified Data Analyst Course in Turkey. The curriculum integrates real-world projects and case studies, ensuring participants gain practical experience and proficiency in data analytics techniques and tools.

DataMites offers flexible learning methods for its data analytics courses in Turkey, providing participants with the choice between Online Data Analytics Training in Turkey and Self-Paced Training. This allows learners to select the approach that best suits their schedule and preferred style of learning.

For data analytics training sessions, participants must present a valid photo ID, such as a national ID card or driver's license. This is essential for receiving the participation certificate and scheduling any relevant certification exams.

Data analytics career mentoring sessions in Turkey are structured to provide personalized guidance. They typically include one-on-one discussions with experienced mentors, covering topics like skill development, industry insights, and career planning. 

Yes, the Certified Data Analyst Course by DataMites is highly valuable in Turkey. It stands out as the most comprehensive non-coding data analytics course, making it accessible for those without technical backgrounds. The program includes a 3-month internship in an AI company, providing practical experience and an experience certificate. With expert faculty guidance and prestigious IABAC Certification, it ensures a well-rounded education for a successful data analytics career in Turkey.

DataMites offers internship opportunities with the Certified Data Analyst Course in Turkey. Through exclusive partnerships with prominent Data Science companies, learners get a chance to apply their knowledge in real-world scenarios. The internships, guided by dedicated DataMites experts and mentors, allow participants to develop valuable data models, adding tangible value to businesses and gaining practical experience in the field.

Yes, DataMites' Data Analyst Course in Turkey incorporates practical learning with 5+ Capstone Projects and a Client/Live Project, offering participants hands-on experience for a comprehensive understanding of data analytics in real-world contexts.

If you miss a DataMites data analytics session in Turkey, worry not. We provide recorded sessions, ensuring you can catch up on the valuable content at your own pace.

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.

View more

OTHER DATA ANALYST TRAINING CITIES IN TURKEY

Global DATA ANALYTICS COURSES Countries

popular career ORIENTED COURSES

DATAMITES POPULAR COURSES


HELPFUL RESOURCES - DataMites Official Blog