on the knowledge of the Data+ certification and enables you to demonstrate your knowledge in advanced data processing, cleaning, and statistical modelling concepts. You will demonstrate your knowledge of machinelearning, industry trends and use of specialised data science applications. You will also apply mathematical and statistical methods appropriately. Step 5 is not a requirement for our job More ❯
all accessible anytime, anywhere, through our easy-to-use online platform. Step 2: Full-Stack AI Mastery Dive deeper with in-demand technical skills including Python programming, data handling, machinelearning, and version control with Git and GitHub. You’ll work on hands-on mini projects that mirror real-world challenges, helping you build confidence and a strong More ❯
from beginner level all the way through to being qualified to work in a junior Data Scientist role. Through the interactive courses, you will gain knowledge in Python, R, MachineLearning, AI , and much more. You will also complete mini projects to gain practical experience and test your skills while you study. Step 2 - CompTIA Data+ CompTIA Data+ More ❯
and operate platform capabilities supporting batch, streaming, and AI-driven workloads Develop resilient and scalable systems using Apache Kafka, Flink, Pulsar, and cloud-native technologies Collaborate with AI/ML teams to deploy models and enable generative AI use cases Implement integrations with data lakes and event stores to enable real-time data flow Contribute fullstack features, including React-based … in Python Experience with Apache Kafka, Flink, and Pulsar for building distributed data pipelines Familiarity with scalable data storage and data lake integrations Proven ability to integrate AI/ML models and work with prompt-based applications Fullstack development skills including React Strong experience with CI/CD, branching strategies, and release automation Comfortable delivering high-quality solutions in a … fast-paced, production environment Preferred Skills Experience working in international and distributed teams Familiarity with cloud-agnostic architectures Exposure to observability tools and practices Background in AI/ML enablement initiatives More ❯
