
Coursera — DeepLearning.AI
Principles of supervised machine learning By in-depth look at regression and classification methods. Gain practical skills in model training and evaluation. Learn to use algorithms for predictive analytics.
Linear RegressionRegularization to Avoid OverfittingLogistic Regression for ClassificationGradient DescentSupervised Learning
gain expertise in Technical Support Fundamentals, mastering troubleshooting, effective customer communication, and problem-solving techniques. Develop a strong foundation in hardware and software support
Binary CodeCustomer SupportLinuxTroubleshooting
Certificate in "Build LookML Objects in Looker" validates proficiency in constructing LookML models within Looker, empowering data analysts to create robust data models for business intelligence.
MLAILookMLSQLData AnalysisData Visualization
Learners develop a deep understanding of agentic AI architectures, including multi-agent collaboration, memory systems, feedback loops, and real-time tool integrations. Through 8 real-world projects, students build advanced AI systems capable of web search, file handling, Python execution, and automated decision-making — similar to real digital assistants or AI copilots.
AIAgenticMCP
This advanced course guides experienced software developers through the transition from developer to solution architect. It covers the architecture of large-scale systems, deep dives into non-functional requirements (performance, scalability, reliability, security), and the internal workings of key tools and platforms like Node.js, Redis, Kafka, Cassandra, ELK, Hadoop, Docker, and Kubernetes. By the end you’ll understand how to make meaningful architectural decisions, build high-performance production systems, and lead system design with confidence.
Software ArchitectureSystem DesignSystem ArchitectureSoftware Engineering