Alexander Afriyie (Alexander A.) is a lecturer, private investigator, journalist, author, course content developer, cyber security and Artificial Intelligent (AI) expert. With such credentials, he has become an authority in his fields with knowledge and experience that truly stands out.
Alexander Afriyie, also known as Alexoo or Prof by his buddies, is an author who has written more than 500 books and online courses.
Alexander Afriyie (Alexander A.) is currently pursuing PhD in Business Management.
He is an accomplished academic, having earned multiple master's degrees from the University of Maryland Global Campus in both Master of Science in Cyber Security and master's in business administration in USA. Alexander studied a Bachelor of Arts degree in Religious Studies and History at the University of Ghana, Legon. Additionally, the biographer has obtained a Bachelor of Arts Degree in Communication Studies with a major in Journalism from the Ghana Institute of Journalism (GIJ). Furthermore, he has a Higher National Diploma in Hotel Catering and Institutional Management (HCIM) from Kumasi Polytechnic. He has Diploma in Media Law and Ethics from the United Kingdom. The author's academic background began at Kumawu Anglican School where he attended from Class One to Form Four; then progressed to Tweneboa Kouda Senior School in Kumawu for his "O" levels. Subsequently, Alexander completed his "A" Levels privately at Kumasi Workers College.
His vast repertoire of works includes academic books about cyber security, management, financials, artificial intelligence, catering, story books, and history books. As a highly accomplished writer, Alexander Afriyie is also the CEO of several companies such as America Street Thinkers, Lexisv.com, udeme.us, CKC.institute.com, pettutor.us, petcoach.us, Certifiedcourses.com, ghanacrimereport.com ,apextechtraining.com, Readonline.us, booksghana.com , pupilslibrary.us, pupilslibrary.com, Healthcaretraining.us, dogbasicsinfo.us.
Introduction
Welcome to the training course on Big Data Modelling and Management Systems. The purpose of this course is to provide an understanding of the principles of big data modelling, management systems, and their applications in solving real-world problems. Through a combination of lecture, discussion, and practical exercises, you will gain a comprehensive overview of big data manipulation techniques and tools.
You will learn how to implement effective solutions to build sustainable models for your organization's data. Furthermore, you will be exposed to the best practices and industry standards related to data governance, quality assurance processes, as well as advanced analytics.
By the end of this course, you should be able to use big data modelling approaches confidently in order to improve organizational performance.
Objectives
1. To provide participants with an understanding of the fundamentals of Big Data Modelling and Management Systems.
2. To develop participant's skills in using data management tools to analyse, organize, and store data for maximum efficiency.
3. To learn about best practices when designing and implementing Big Data models for better performance and scalability.
4. To equip participants with the knowledge of how to integrate different applications into a cohesive system that leverages organizational data resources efficiently.
5. To be able to measure, monitor, and track performance metrics from a variety of sources as part of managing structural complexity associated with Big Data analytics projects.
Course Outline
Module 1: Overview of Big Data and Modelling
• Understanding of the fundamentals of Big Data Modelling and Management Systems.
• Introduction to Big Data & its sources
• Understanding the key features of Big Data & why it is important
• Overview of different modelling techniques used in Big Data
• Overview of big data tools
• Understanding the importance of data pre-processing
•Skills in using data management tools to analyse, organize, and store data for maximum efficiency.
Module 2: Working with Different Types of Database Structures
• Database fundamentals & basic SQL commands
• Understanding NoSQL databases and usage Scenarios
• Working with Apache Hadoop Distributed File System (HDFS)
Module 3: Granularizing, Normalizing, and Summarizing Big Data
• Techniques for granularizing large datasets for analysis
• Extracting information from unstructured data sources
• Working with normalization methods such as z-score standardization & min-max scaling
• Applying feature extraction techniques such as principal component analysis (PCA)
Module 4: Building a Big Data Modelling System
• Implementing predictive analytics using machine learning algorithms
• Utilizing various big data analytics tools e.g., Apache Spark, Google Cloud Platform (GCP), etc.
• Creating a data pipeline architecture for model building
• Exploring best practices associated with model management systems
• Best practices when designing and implementing Big Data models for better performance and scalability.
• Exposed to the best practices and industry standards related to data governance, quality assurance processes, as well as advanced analytics.
• Using supervised & unsupervised learning techniques to evaluate models
Module 5: Assessing and Deploying a Model Management System
Título : Big Data Modeling and Management Systems
EAN : 9798223343103
Editorial : Alexander Afriyie
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