Big Data Professional Program
| Preference | Dates | Timing | Location |
|---|---|---|---|
| In-Person and Live Webinars | To be confirmed | To be confirmed | Dubai Knowledge Park |
Course Description
The Big Data Professional Program is designed to equip participants with the skills and tools needed to build, manage, and optimize scalable big data pipelines in today’s data-driven world. Whether you’re a data engineer, data analyst, or aspiring data scientist, this course offers hands-on experience with the most in-demand technologies, including Hadoop, Apache Spark, Kafka, and Tableau.
Through real-world projects and use cases, participants will master the end-to-end implementation of big data solutions—starting from ingestion, processing, and analysis to visualization and reporting. With an emphasis on emerging trends like cloud-based solutions, real-time data streaming, and machine learning integration, this course prepares you to tackle the challenges of modern big data ecosystems.
Course Outline
Audience
Prerequisites
Learning Outcomes
Course Outline
Unit 1: Big Data Foundations
- Overview of Big Data and Emerging Challenges
- The Hadoop Ecosystem: HDFS, YARN, and MapReduce
- Setting Up a Hadoop Cluster
Unit 2: Core Hadoop Components
- HDFS: Distributed Storage and File Management
- MapReduce: Parallel Processing for Large-Scale Data
- Hands-on Project: Processing Log Files with HDFS and MapReduce
Unit 3: Apache Spark for Big Data Processing
- Introduction to Apache Spark: RDDs, DataFrames, and Datasets
- Advanced Data Manipulation with Spark SQL
- Hands-on Project: Aggregating and Filtering the MovieLens Dataset
Unit 4: Advanced Spark Techniques
- Spark Streaming: Real-Time Data Processing with Kafka
- Machine Learning with Spark MLlib: Building a Recommender System
- Hands-on Project: Streaming and Predicting User Behavior
Unit 5: Data Visualization with Tableau
- Connecting Big Data Sources (HDFS, Spark SQL) to Tableau
- Building Interactive Dashboards and Reports
- Automating Data Publishing with the Tableau Hyper API
- Hands-on Project: Visualizing Top Movie Trends and Insights
Unit 6: Integrating Relational and Non-Relational Databases
- Using Hive and SQL to Query Big Data
- NoSQL with HBase: Managing Semi-Structured Data
- Hands-on Project: Migrating Data from MySQL to HDFS
Unit 7: Cloud-Based Big Data Solutions
- Introduction to Cloud Platforms: AWS, Google Cloud, Azure
- Implementing Big Data Solutions in the Cloud
- Hands-on Project: Deploying a Scalable Data Pipeline in a Cloud Environment
Unit 8: Data Ethics and Governance
- Principles of Data Governance
- Ethical Considerations in Big Data
- Compliance with Data Protection Regulations (e.g., GDPR)
- Case Studies on Ethical Data Use
Unit 9: Emerging Technologies in Big Data
- Integration of AI and Big Data
- Edge Computing and Its Applications
- Big Data in the Internet of Things (IoT)
- Hands-on Project: Analyzing IoT Data Streams
Unit 10: Final Capstone Project
Participants will design and implement a comprehensive big data pipeline:
- Ingest Data using Kafka or Flume.
- Process Data with Spark for real-time and batch analysis.
- Implement Machine Learning models using Spark MLlib.
- Deploy the solution on a cloud platform.
- Visualize Data in Tableau dashboards.
- Present findings, discuss scalability, performance, and business impact.
Audience
- Data analysts and aspiring data scientists looking to learn how to process Big Data using Apache Spark.
- Software engineers and programmers aiming to understand the broader Big Data ecosystem and use it for storing and analyzing massive datasets.
- Project, program, or product managers seeking a high-level understanding of Big Data architecture and components.
Prerequisites
- Experience with Python programming, and machine learning, or successful completion of our Artificial Intelligence Professional Program.
Learning Outcomes
- Build end-to-end big data solutions for ingesting, storing, processing, and visualizing large datasets.
- Process massive datasets using tools like Hadoop, Apache Spark, and Spark SQL.
- Apply machine learning techniques to create recommender systems and predictive models using Spark MLlib.
- Gain practical experience in real-time data processing with Spark Streaming and Kafka.
- Deploy big data solutions in cloud environments such as AWS, Google Cloud, or Azure.
- Create interactive dashboards to present data insights effectively using Tableau.
By completing this course, participants will gain hands-on experience and foundational knowledge to thrive in today’s data-driven industries.
Testimonials
The workshop on big data and machine learning was an excellent introduction to practitioners considering using data science. Ahmed demonstrated considerable teaching talent rooted in his long expertise with systems development.
Very rewarding course. Rare to find a Deep learning course in Dubai that teaches concepts from scratch and provides practical applications. Will definitely recommend.
Innosoft Gulf Institute is educating students breaking and revolutionary techniques with focus on future trends in CIT industry. Mr. Ahmed is well updated on latest technologies related to Big Data, AI, Machine Learning, etc.
Rated as 5 star in terms of overall deliverance.
