Analysing Big Data
The Big Data Analytics course is designed for data scientists that want to start working with big data technologies. The course is focused on 3 main objectives to give students the capability to start their own Big Data Analytics projects:
- Give a clear understanding of the differences between the Big Data projects and technologies, to the traditional relational approaches;
- Give a solid and practical understanding of what Spark is, with practical data integration use cases (both structured and unstructured) to prepare data for Data Science processes;
- Explore the SparkML library for Data Science use cases.
Analyzing and Visualizing Data
This course unit’s goal is to provide students the ability to:
- Gather and transform data from multiple sources;
- Discover and combine data;
- Explore, analyze, and visualize data;
- Transform data into insights;
- Create and share dashboards;
- Use natural language queries;
- Create real-time dashboards.
Big Data Foundations
The main goal of the course unit is to introduce students to the batch, near real time and real times Big Data stacks, allowing them to build processing solutions to gather, cleanse, reshape and store data for analysis. The course unit will cover technologies within the core Hadoop ecosystem but also modern streaming solutions, based on managed platforms. The course has a practical, hands-on approach and students will learn to implement low-latency real world solutions.
Deep Learning Neural Networks
This course unit introduces deep learning. Students taking this course will learn the theories, models, algorithms, implementation and recent progress of deep learning, and obtain empirical experience on training deep neural networks. Specifically, the course will cover basic concepts in optimization, neural networks, convolutional neural networks (CNN), and recurrent neural networks (RNN). By the end of the course, it is expected that students will have a strong familiarity with the subject and be able to design and develop deep learning models for a variety of tasks.
Enterprise Data Science Bootcamp
The main goal of the Enterprise Data Science Bootcamp is to give the students an intensive team challenge that will give them practical, hands-on experience working directly with enterprise scenarios. Enterprise partners will provide the teams with challenges based on real world scenarios. The teams should apply analytics and Big Data competencies covered in the program to uncover actionable insights and drive innovation.