Data Gathering and Management:
This module focuses on skills for collecting, cleaning, and preprocessing data. Students learn to work with both structured and unstructured data, manage databases, utilize APIs, and create data pipelines.
Analytical Programming:
Emphasizing programming languages such as Python and SQL, this area covers the essential tools for data analysis, statistical modeling, and task automation.
Data Visualization:
Students learn to create impactful visual representations of data, facilitating insight discovery and effective communication of findings. Key tools include Excel, Power BI, Tableau, Matplotlib, and Seaborn.
Machine Learning:
This component covers the development of models to predict outcomes, detect patterns, and inform decision-making. Students explore supervised, unsupervised, and reinforcement learning techniques using frameworks like Scikit-Learn, TensorFlow, and PyTorch.
Model Deployment:
Participants learn how to transition machine learning models from development to production, gaining skills in cloud computing, APIs, containerization (Docker), and DevOps practices.
THRIVE (Soft Skills):
Recognizing the importance of soft skills in data science, this program includes training in communication, teamwork, problem-solving, adaptability, and leadership, ensuring students are well-rounded professionals ready to thrive in their careers.
The Microsoft Azure certification program equips IT professionals with the skills to design, deploy, and manage applications and services on the Azure platform.
Azure Fundamentals:
Participants gain foundational knowledge of cloud concepts, core Azure services, and pricing and support models, providing a solid base for further learning.
Azure Architecture:
This module covers the principles of cloud architecture, including designing scalable, resilient, and highly available applications within the Azure environment.
Azure Networking:
Students learn to implement and manage Azure networking services, including virtual networks, load balancers, and VPN gateways, ensuring secure communication within cloud resources.
Azure Storage Solutions:
This area focuses on implementing Azure storage solutions, exploring different types of storage, data redundancy options, and access management.
Identity and Access Management:
Participants learn to manage Azure Active Directory (AD) and implement role-based access control (RBAC) to secure resources and manage identities effectively.
Azure Security:
This module emphasizes best practices for securing Azure environments, covering threat protection, security management, and compliance considerations.
Monitoring and Troubleshooting:
Students gain skills in monitoring Azure resources, implementing logging and diagnostics, and troubleshooting common issues to ensure optimal performance.
DevOps Practices in Azure:
This area introduces participants to DevOps principles, CI/CD pipelines, and automation tools within the Azure platform, fostering a culture of continuous improvement and collaboration.
Data Solutions:
Participants explore Azure's data solutions, including Azure SQL Database, Cosmos DB, and data analytics services, enabling them to implement effective data management strategies.
The CEH program provides comprehensive training in ethical hacking techniques and methodologies, empowering professionals to think like hackers to better defend against cyber threats.
Ethical Hacking Fundamentals:
Participants gain a solid understanding of the principles and concepts of ethical hacking, including the ethical and legal considerations involved in penetration testing.
Footprinting and Reconnaissance:
This module covers techniques for gathering information about targets to identify potential vulnerabilities. Students learn to utilize various tools and techniques for effective reconnaissance.
Scanning Networks:
Participants learn how to perform network scanning to discover live hosts, open ports, and services. This includes using tools for vulnerability scanning and assessment.
Enumeration:
This area focuses on extracting detailed information about systems, users, and services to identify potential attack vectors.
System Hacking:
Students explore methodologies for compromising systems, including password cracking, privilege escalation, and maintaining access while ensuring stealth and persistence.
Malware Threats:
This module covers various types of malware, their methods of delivery, and techniques for detecting and mitigating these threats.
Sniffing and Social Engineering:
Participants learn about network sniffing techniques and the psychological aspects of social engineering attacks, equipping them to recognize and defend against these tactics.
Web Application Hacking:
This area focuses on identifying and exploiting vulnerabilities in web applications, including SQL injection, cross-site scripting, and security misconfigurations.
Wireless Network Hacking:
Students explore vulnerabilities in wireless networks and the techniques used to secure them, including encryption standards and access controls.
Cloud Computing and Security:
This module introduces participants to cloud security concepts, threats, and best practices, highlighting the importance of securing cloud environments.