Learn the concepts of Big Data!
Eligible CPF and multi-financing up to 100%
To be recalled Access to the programmeApproach 3P
Our training centre guides you in identifying the ideal training, helping you maximize funding opportunities.
We put all the keys in hand for a start with confidence.
Experience an immersive and intensive training experience, designed to dive into practical workshops and real case studies.
Learn by doing, and develop concrete skills directly applicable to your future projects.
At the end of your career, we evaluate your acquired skills, issue certification attesting to your expertise, and accompany you to ensure your success in your professional projects.
You are now ready to excel!
Description of the training
This course presents the field of Big Data, Big Data architectures, analysis, data science, artificial intelligence (IA) and Big Data visualization.
Objectives of training
At the end of this training, participants will be able to:
Understand the basics of Big Data and its key concepts.
Acquire practical skills in massive data management with Hadoop and HDFS.
Mastering data processing techniques with Apache Spark.
Learn how to analyze and visualize data with tools such as Spark SQL and Tableau.
Understanding data security and governance issues in Big Data environments.
Who is this training for?
The "Exploring Big Data" training is intended for a wide audience, including:
Developers and Data Engineers;
Data analysts;
IT Managers and Project Managers;
Data Scientists;
Students and professionals or consultants in reconversion.
Prerequisites
Basic knowledge of information systems.
Programme
The training programme is structured around several main modules:
Challenges for Big Data and its Ecosystem
- Introduction to Big Data and its Ecosystem
- Presentation of Big Data's main tools: Hadoop, Spark, NoSQL
- Big Data Architecture: HDFS, YARN, MapReduce
- Use cases in various sectors: service, finance, transport, etc.
- Exploration of Hadoop and HDFS
- Data handling in HDFS: basic commands (copy, move, list files).
- Practical case: Setting up a Hadoop cluster and data management via HDFS.
- Introduction to Apache Spark and its real-time processing
- Introduction to RDDs (Resilient Distributed Datasets) and DataFrames.
- Practical case: Data processing with Spark (e.g. data processing and cleaning).
- Data Analysis with Spark SQL
- Presentation of SBMD and its integration with Spark for data analysis.
- Introduction to Data Visualization: Using Tableau or Power BI to create reports and dashboards.
- Visualisation of data
- Practical case: Execution of queries on a data set with Spark SQL and creation of interactive visualizations
Training assets
Pedagogical approach alternating theory and practice.
Qualified trainers with experience in Big Data.
Access to modern teaching tools and resources.
Training accessible to all, without advanced technical prerequisites.
Pedagogical methods and tools used
Live demonstrations on Big Data services (Hadoop, Spark).
Real case studies and practical group work.
Integration simulations and massive data transformation.
Feedback on the challenges faced in real projects.
Evaluation
The evaluation is carried out in a number of ways:
QCM to test the understanding of concepts.
Practical case studies to apply knowledge.
Ongoing evaluation during practical sessions.
Certification: Certificate of success in training with certification for those who have successfully completed the final evaluation.
Normative References
Compliance with standards:
Certification of training according to national and European standards.
Compliance with data management and security regulations.