This training is for professional development purposes. The certificate obtained does not replace the MYK authorization certificate required for trainings that mandate MYK authorization.

Training Objective

The Big Data Analysis Training Program aims to equip participants with the skills necessary to understand, process, and analyze large datasets. The course teaches how to extract valuable insights from big data using data mining, machine learning, and analytical tools.

Training Content

• 1. Big Data Fundamentals and Concepts
• What is Big Data?: Definition, characteristics, and business applications
• Big Data Features: Variety, Velocity, Volume, Veracity, Value (5Vs)
• Types of Big Data: Structured, semi-structured, and unstructured data
• Big Data Ecosystem: Technologies like Hadoop, Spark, NoSQL
• 2. Introduction to Big Data Analysis
• Data Collection and Storage: Gathering and storing data on big data platforms
• Data Processing Methods: Differences between batch and stream processing
• Data Preprocessing: Cleaning, integration, and transformation
• Data Formats and Storage Systems: Parquet, Avro, JSON, and systems like HDFS, Amazon S3
• 3. Data Mining and Analytical Methods for Big Data
• Data Mining Basics: Classification, clustering, association analysis, regression analysis
• Advanced Data Analysis Techniques: Time series, statistical analysis, and machine learning algorithms
• Machine Learning and AI: Supervised and unsupervised learning, decision trees, k-means, regression, classification
• 4. Big Data Analysis with Hadoop and Spark
• Hadoop Ecosystem: HDFS, MapReduce, YARN
• Apache Spark: RDDs, DataFrames, Spark SQL, MLlib, Spark Streaming
• Differences between Hadoop and Spark
• Application development and processing acceleration
• 5. NoSQL Databases and Big Data Analysis
• NoSQL Databases: MongoDB, Cassandra, HBase, CouchDB
• Differences between NoSQL and SQL
• Data management and advanced NoSQL usage
• 6. Data Visualization and Reporting
• Data Visualization for Big Data: Analysis with Power BI
• Interpreting and reporting big data
• Interactive reports
• 7. Big Data Security and Ethics
• Data Security: Encryption and authorization
• Data Privacy and Ethics: Anonymization and legal compliance
• Data breaches and risk management
• 8. Big Data Applications and Real-World Scenarios
• Financial sector applications
• Big Data in healthcare
• E-commerce and marketing
• IoT and Big Data
• 9. Big Data and Cloud Technologies
• Cloud computing and Big Data: Using AWS, Azure, GCP
• Data storage and computation
• Cloud-based solutions for Big Data
• 10. Skills and Certifications Gained
• Expertise in Big Data analysis
• Machine learning and statistical analysis
• Expertise in Big Data tools: Hadoop, Spark, NoSQL
• Internationally recognized certifications

The training is open to corporate collaborations (packages for institutions/companies); individual applications are not accepted. The training content can be adjusted according to the participant profile and needs. After mutual discussions, the training scope and method (On-site, Online) are determined and the relevant processes are completed. Upon agreement, schedules, times, and training locations are coordinated with the participants and instructors.