This training is for professional development purposes and the certificate awarded does not replace the MYK certification required for training where MYK certification is mandatory.

Data Analyst Training

Training Duration: 10 Days (09:00–12:00 Theory, 13:00–16:00 Practice)
Level: Beginner + Intermediate/Advanced

Participant Profile

• University students and recent graduates
• Professionals working with data in fields like business, economics, engineering, healthcare, etc.
• Employees in public institutions (municipalities, governorships, etc.) and private sector requiring data analysis skills
• Managers and administrative staff looking to contribute to data-driven decision-making processes

Prerequisites / Requirements

• Basic programming knowledge (can be provided with preparation courses)
• Basic knowledge of statistics and mathematics
• Ability to follow technical English resources (recommended)

Curriculum

Week 1: Beginner Level

Day 1: Introduction to Data Analytics
• The role of a data analyst and its importance in business
• Types of data (numerical, categorical, textual) and data sources
• Data lifecycle

Day 2: Data Preparation and Cleaning
• Handling missing data and data imputation methods
• Data standardization, normalization, outliers
• Hands-on data cleaning exercises

Day 3: Basic Statistics and Probability
• Mean, median, mode, variance, standard deviation
• Correlation vs causality
• Hands-on basic statistical analyses

Day 4: Data Visualization
• Types of graphs and their use cases (bar, line, scatter, box plots)
• Creating tables and visualization principles
• Dashboard concepts and examples

Day 5: Mini Project – Basic Analysis
• Analyzing and visualizing a small dataset
• Group presentations and evaluation

Week 2: Intermediate / Advanced Level

Day 6: Introduction to Databases and SQL
• Database logic, relational databases
• Basic SQL queries (SELECT, WHERE, GROUP BY, JOIN)
• Hands-on SQL exercises

Day 7: Data Analysis with Programming
• Data processing with Python or R
• Introduction to data libraries (pandas, numpy, ggplot – conceptual level)
• Basic data analysis applications

Day 8: Business Intelligence and Reporting
• Concept of business intelligence
• Conceptual use of tools like Power BI, Tableau
• Contribution to reporting and decision support systems

Day 9: Advanced Statistical Methods
• Regression analysis, hypothesis testing
• Time series analysis and forecasting awareness
• Practical exercises with real-world datasets

Day 10: Final Project – Applied Data Analysis
• Participants analyze a dataset relevant to their field
• Visualization and reporting
• Presentation and evaluation

Training Outcomes

• Participants will gain skills in data preparation, analysis, and visualization.
• Introduction to SQL and programming-based data analysis.
• Learn business intelligence and reporting concepts.
• Gain project experience with real-world datasets.
• Apply statistical methods to business and academic contexts.

Training Notes

• The instructor can tailor the content to participants' profiles.
• The program is independent of technology, focusing on core principles.
• Upon completion, participants will receive a university-approved certificate.

This training is open to institutional collaborations (corporate/organizational packages), and individual applications are not accepted. The training content can be adjusted based on the institutional participant profile and needs. After mutual discussions, the scope and method of the training (in-person, online) will be determined, and the relevant processes will be completed. If an agreement is reached, suitable days and times for your institution's participants and our instructors will be set, and the location for the training will be determined.