Certificate in Advanced Big Data and Data Analytics (CABDDA)
5 DaysCertificate in Advanced Big Data and Data Analytics (CABDDA) - Virtual Learning
Course Methodology
This course will be highly technical with group discussions, hands-on practical exercises, and group activities being the core focus.
Course Objectives
By the end of the course, participants will be able to:
- Understand key big data technologies, including a deep dive into Apache Spark
- Describe the main challenges and advantages of Hadoop map-reduce
- Demonstrate and discuss key technologies for big data storage and compute, such as PostgreSQL and object storage
- Discuss popular machine learning algorithms, deep learning techniques and the importance of ethics in data analytics and artificial intelligence
- Deliver a presentation demonstrating the analytics lifecycle and Spark
Target Audience
This is an advanced level course. It is expected that participants either have a number of years of experience utilizing big data, or have previously attended the Certified Big Data and Data Analytics Practitioner (CBDDAP) course. This course is ideal for data engineers, AI engineers and data scientists. Recommended pre-knowledge includes some python programming experience and data visualization practice.
Target Competencies
- Big data utilization
- Big data analytics structures and technologies
- Ethics and integrity for big data and AI development
- Big data storage
- Apache Spark best practices
Course Outline
- Big Data Analytics Use Cases
- How can big data projects meet organizational needs
- Big data examples:
- Netflix
- Orbitz
- Dell
- Others
- Best practices in project design
- Assessing the current state of your organization
- Choosing datasets for course projects
- Storing Big Data
- Big data architectures and paradigms
- The Hadoop Ecosystem
- Overview of Hadoop
- Hadoop Distributed File System (HDFS)
- Massively parallel processing (MPP) versus distributed in-memory applications
- RDBMSs vs NoSQL DBs
- PostgreSQL
- MongoDB
- Cassandra
- Streaming data
- The Hadoop Ecosystem
- Data-warehousing versus Data Mart
- Intro to Apache Spark
- Big data SQL hands-on-labs
- Big data architectures and paradigms
- Computing Big Data
- How to access big data
- Role of cloud computing
- Data movement risk
- Networking and co-location
- Apache Spark lab
- Big data extract, transform, load (ETL) big data compute technologies
- Distributed compute
- High performance clusters vs Apache Spark
- Streaming: Storm, Spark structured streaming
- Apache Spark ETL labs
- Apache Spark data engineering
- How to access big data
- Big Data Advanced Analytics and AI
- Analytics Lifecycle
- Apache Spark vs Pandas
- Big data machine learning & deep learning in Spark
- Importance of ethics in AI
- Automl & Hyperparameter tuning
- Course Big Data Projects
- Identify analytical opportunities in an organization
- Define and assess the problem
- Describe the impact and use of data to address the problem
- Identify potential data sources
- Design a data analytics project
- Access, explore, analyze and visualize chosen dataset for project
- Present project insights in course
- Identify analytical opportunities in an organization
Mawred Certificate
Mawred Certificate courses by Al mawred Training & Consulting are designed for those willing to challenge themselves and go the extra distance...
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Virtual Schedule
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