Overview
Join our comprehensive course and unlock boundless opportunities for personal and professional growth with our meticulously crafted comprehensive course. If you yearn for precise knowledge that not only enriches your personal and professional life but also empowers you to excel and stand out, then look no further.Â
Our in-depth course provides a learning experience meticulously designed to empower individuals from diverse backgrounds. It also provides exclusive and interactive learning materials and is developed with the utmost dedication to help you bring out the best version of yourself. During the process of learning from our course, you will be able to recognise and monitor your growth as well as reflect on your experiences.
Whether you’re a professional seeking to elevate your career prospects, a curious student hungry for knowledge expansion, or an aspiring enthusiast pursuing a newfound passion, this course is tailor-made to cater to your unique needs.
So, don’t delay any further and enrol now!
Learning Outcome
By the end of this course, you will be able to:
- Develop a comprehensive understanding of course-related concepts and principles.
- Apply critical thinking and problem-solving skills to overcome any possible challenges.
- Foster a commitment to continuous learning and personal growth.
- Improve communication skills for effective expression and discussion of course-related ideas.
- Engage with a variety of information and enhance information literacy skills.
- Collaborate and work efficiently in team-based projects and discussions, where applicable.
- Utilise technology and digital tools effectively to support course-related tasks and objectives.
- Embrace ethical conduct and responsibility in professional settings.
- Develop a growth mindset and adaptability, embracing lifelong learning and skill enhancement.
Who Is This Course For?
If you contemplate a suitable niche or want to experience the primary to advanced level knowledge of this industry, then this course is for you. Regardless of your background, you can participate and enhance your CV.
Certificates
You will earn a CPD QS certificate upon completing this course. It will not only serve as a concrete validation of the knowledge and skills acquired during the course but it will also enhance your professional credibility and open doors to new opportunities and career advancement.
Certificate of Completion
Digital Certificate
Price: £4.99
The digital Certificate of Completion will be provided after learners complete the course.
Hardcopy Certificate of Completion
Hard Copy Certificate
Price: £9.99
The hardcopy certificate for all individual titles can be received by paying £9.99 each, for students living inside the UK.
International Students
For international orders, the total fee is £14.99 (£9.99 Certification Fee + £5 postal charge) for each individual titles.
Requirements
This course has no set requirements for learning. All you need is a smart device, a reliable internet connection, and a basic command of English and you’re good to go!
Career Path
This career-friendly course will deepen your insights into the UK job market and help you secure your dream job with time. You will be able to experience noticeable development in your current career.Â
It’s time to unlock limitless opportunities.
Course Curriculum
| Section 01: Introduction | |||
| Introduction | 00:07:00 | ||
| Building a Data-driven Organization – Introduction | 00:04:00 | ||
| Data Engineering | 00:06:00 | ||
| Learning Environment & Course Material | 00:04:00 | ||
| Movielens Dataset | 00:03:00 | ||
| Section 02: Relational Database Systems | |||
| Introduction to Relational Databases | 00:09:00 | ||
| SQL | 00:05:00 | ||
| Movielens Relational Model | 00:15:00 | ||
| Movielens Relational Model: Normalization vs Denormalization | 00:16:00 | ||
| MySQL | 00:05:00 | ||
| Movielens in MySQL: Database import | 00:06:00 | ||
| OLTP in RDBMS: CRUD Applications | 00:17:00 | ||
| Indexes | 00:16:00 | ||
| Data Warehousing | 00:15:00 | ||
| Analytical Processing | 00:17:00 | ||
| Transaction Logs | 00:06:00 | ||
| Relational Databases – Wrap Up | 00:03:00 | ||
| Section 03: Database Classification | |||
| Distributed Databases | 00:07:00 | ||
| CAP Theorem | 00:10:00 | ||
| BASE | 00:07:00 | ||
| Other Classifications | 00:07:00 | ||
| Section 04: Key-Value Store | |||
| Introduction to KV Stores | 00:02:00 | ||
| Redis | 00:04:00 | ||
| Install Redis | 00:07:00 | ||
| Time Complexity of Algorithm | 00:05:00 | ||
| Data Structures in Redis : Key & String | 00:20:00 | ||
| Data Structures in Redis II : Hash & List | 00:18:00 | ||
| Data structures in Redis III : Set & Sorted Set | 00:21:00 | ||
| Data structures in Redis IV : Geo & HyperLogLog | 00:11:00 | ||
| Data structures in Redis V : Pubsub & Transaction | 00:08:00 | ||
| Modelling Movielens in Redis | 00:11:00 | ||
| Redis Example in Application | 00:29:00 | ||
| KV Stores: Wrap Up | 00:02:00 | ||
| Section 05: Document-Oriented Databases | |||
| Introduction to Document-Oriented Databases | 00:05:00 | ||
| MongoDB | 00:04:00 | ||
| MongoDB Installation | 00:02:00 | ||
| Movielens in MongoDB | 00:13:00 | ||
| Movielens in MongoDB: Normalization vs Denormalization | 00:11:00 | ||
| Movielens in MongoDB: Implementation | 00:10:00 | ||
| CRUD Operations in MongoDB | 00:13:00 | ||
| Indexes | 00:16:00 | ||
| MongoDB Aggregation Query – MapReduce function | 00:09:00 | ||
| MongoDB Aggregation Query – Aggregation Framework | 00:16:00 | ||
| Demo: MySQL vs MongoDB. Modeling with Spark | 00:02:00 | ||
| Document Stores: Wrap Up | 00:03:00 | ||
| Section 06: Search Engines | |||
| Introduction to Search Engine Stores | 00:05:00 | ||
| Elasticsearch | 00:09:00 | ||
| Basic Terms Concepts and Description | 00:13:00 | ||
| Movielens in Elastisearch | 00:12:00 | ||
| CRUD in Elasticsearch | 00:15:00 | ||
| Search Queries in Elasticsearch | 00:23:00 | ||
| Aggregation Queries in Elasticsearch | 00:23:00 | ||
| The Elastic Stack (ELK) | 00:12:00 | ||
| Use case: UFO Sighting in ElasticSearch | 00:29:00 | ||
| Search Engines: Wrap Up | 00:04:00 | ||
| Section 07: Wide Column Store | |||
| Introduction to Columnar databases | 00:06:00 | ||
| HBase | 00:07:00 | ||
| HBase Architecture | 00:09:00 | ||
| HBase Installation | 00:09:00 | ||
| Apache Zookeeper | 00:06:00 | ||
| Movielens Data in HBase | 00:17:00 | ||
| Performing CRUD in HBase | 00:24:00 | ||
| SQL on HBase – Apache Phoenix | 00:14:00 | ||
| SQL on HBase – Apache Phoenix – Movielens | 00:10:00 | ||
| Demo : GeoLife GPS Trajectories | 00:02:00 | ||
| Wide Column Store: Wrap Up | 00:04:00 | ||
| Section 08: Time Series Databases | |||
| Introduction to Time Series | 00:09:00 | ||
| InfluxDB | 00:03:00 | ||
| InfluxDB Installation | 00:07:00 | ||
| InfluxDB Data Model | 00:07:00 | ||
| Data manipulation in InfluxDB | 00:17:00 | ||
| TICK Stack I | 00:12:00 | ||
| TICK Stack II | 00:23:00 | ||
| Time Series Databases: Wrap Up | 00:04:00 | ||
| Section 09: Graph Databases | |||
| Introduction to Graph Databases | 00:05:00 | ||
| Modelling in Graph | 00:14:00 | ||
| Modelling Movielens as a Graph | 00:10:00 | ||
| Neo4J | 00:04:00 | ||
| Neo4J installation | 00:08:00 | ||
| Cypher | 00:12:00 | ||
| Cypher II | 00:19:00 | ||
| Movielens in Neo4J: Data Import | 00:17:00 | ||
| Movielens in Neo4J: Spring Application | 00:12:00 | ||
| Data Analysis in Graph Databases | 00:05:00 | ||
| Examples of Graph Algorithms in Neo4J | 00:18:00 | ||
| Graph Databases: Wrap Up | 00:07:00 | ||
| Section 10: Hadoop Platform | |||
| Introduction to Big Data With Apache Hadoop | 00:06:00 | ||
| Big Data Storage in Hadoop (HDFS) | 00:16:00 | ||
| Big Data Processing : YARN | 00:11:00 | ||
| Installation | 00:13:00 | ||
| Data Processing in Hadoop (MapReduce) | 00:14:00 | ||
| Examples in MapReduce | 00:25:00 | ||
| Data Processing in Hadoop (Pig) | 00:12:00 | ||
| Examples in Pig | 00:21:00 | ||
| Data Processing in Hadoop (Spark) | 00:23:00 | ||
| Examples in Spark | 00:23:00 | ||
| Data Analytics with Apache Spark | 00:09:00 | ||
| Data Compression | 00:06:00 | ||
| Data serialization and storage formats | 00:20:00 | ||
| Hadoop: Wrap Up | 00:07:00 | ||
| Section 11: Big Data SQL Engines | |||
| Introduction Big Data SQL Engines | 00:03:00 | ||
| Apache Hive | 00:10:00 | ||
| Apache Hive : Demonstration | 00:20:00 | ||
| MPP SQL-on-Hadoop: Introduction | 00:03:00 | ||
| Impala | 00:06:00 | ||
| Impala : Demonstration | 00:18:00 | ||
| PrestoDB | 00:13:00 | ||
| PrestoDB : Demonstration | 00:14:00 | ||
| SQL-on-Hadoop: Wrap Up | 00:02:00 | ||
| Section 12: Distributed Commit Log | |||
| Data Architectures | 00:05:00 | ||
| Introduction to Distributed Commit Logs | 00:07:00 | ||
| Apache Kafka | 00:03:00 | ||
| Confluent Platform Installation | 00:10:00 | ||
| Data Modeling in Kafka I | 00:13:00 | ||
| Data Modeling in Kafka II | 00:15:00 | ||
| Data Generation for Testing | 00:09:00 | ||
| Use case: Toll fee Collection | 00:04:00 | ||
| Stream processing | 00:11:00 | ||
| Stream Processing II with Stream + Connect APIs | 00:19:00 | ||
| Example: Kafka Streams | 00:15:00 | ||
| KSQL : Streaming Processing in SQL | 00:04:00 | ||
| KSQL: Example | 00:14:00 | ||
| Demonstration: NYC Taxi and Fares | 00:01:00 | ||
| Streaming: Wrap Up | 00:02:00 | ||
| Section 13: Summary | |||
| Database Polyglot | 00:04:00 | ||
| Extending your knowledge | 00:08:00 | ||
| Data Visualization | 00:11:00 | ||
| Building a Data-driven Organization – Conclusion | 00:07:00 | ||
| Conclusion | 00:03:00 | ||
| Assignment | |||
| Assignment -SQL NoSQL Big Data and Hadoop | 00:00:00 | ||
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Offer Ends in
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Access01 Year
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LevelLevel 3
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Students3
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Duration22 hours, 33 minutes