Cloud Security Risks: Identify and Protect Against Threats

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In today's interconnected world, network security is more critical than ever. This Specialization from Google provides you with foundational knowledge of how networks function and how to protect them from attacks. You’ll dive into core concepts like network architecture, protocols, and how to defend against modern cyber threats. You’ll also learn how to utilize powerful tools such as Wireshark, tcpdump, Splunk, and Google SecOps. Google experts will guide you through this Specialization by providing hands-on activities that simulate relevant tasks, teaching you how to: Configure network addresses and understand how data travels through the network Read and interpret network traffic flows to identify suspicious activity Configure network services and understand the difference between a VPN and a proxy Troubleshoot connectivity issues and fix them quickly Harden systems and conduct a basic incident response process Upon completion, you’ll be able to analyze network traffic, recognize common vulnerabilities, and implement strategies to secure both traditional networks and cloud environments.

This specialization equips developers with the essential knowledge and skills to build responsible AI systems by applying best practices of Fairness, Interpretability, Transparency, Privacy, and Safety. Throughout the courses, you will learn how to: Identify and Mitigate Bias: Learn to recognize and address potential biases in your machine learning models to mitigate fairness issues. Apply Interpretability Techniques: Gain practical techniques to interpret complex AI models and explain their predictions using Google Cloud and open source tools. Prioritize Privacy and Security: Implement privacy-enhancing technologies like differential privacy and federated learning to protect sensitive data and build trust. Ensure Generative AI Safety: Understand and apply safety measures to mitigate risks associated with generative AI models. By the end of this specialization, you will have a comprehensive understanding of responsible AI principles and the practical skills to build AI systems that are ethical, reliable, and beneficial to users.

This learning path is designed for security professionals and cloud architects aiming to master the Google Cloud security ecosystem. Learners will progress from foundational AI security frameworks (SAIF) and autonomic security operations to the management of vulnerabilities and risks, focusing on high-impact security operations use cases within Security Command Center. The path concludes with a deep dive into Google SecOps, equipping students to engineer advanced detection rules (SIEM) and automate incident response (SOAR).

This is the seventh course in the Google Cybersecurity Certificate. In this course, learners will be introduced to the Python programming language and learn how to apply it to a security setting to automate tasks. First, learners will focus on key foundational Python programming concepts, including data types, variables, conditional statements and iterative statements. Next, they will learn to work effectively with Python by developing functions, using libraries and modules, and making their code readable. Following this, they will explore working with string and list data. A final component of learning to automate tasks through Python will be an exploration of how to import and parse files, and then the course will conclude with a focus on debugging. By the end of this course, you will: - Explain how the Python programming language is used in cybersecurity. - Write conditional and iterative statements in Python. - Create new, user-defined Python functions. - Use Python to work with strings and lists. - Use regular expressions to extract information from text. - Use Python to open and read the contents of a file. - Identify best practices to improve code readability. - Practice debugging code.