Protect What Matters Most
Master threat detection, ethical hacking, and compliance strategies with Nvidya’s expert-led cybersecurity training. Stay ahead of evolving risks and become the shield your organization needs.
✅ Top Certifications: CEH, CompTIA Security+, CISSP
Lead with Confidence, Deliver with Impact
Gain control over complex projects with PMP®, PRINCE2®, and other top-tier certifications. Learn practical tools and methodologies to drive successful outcomes—on time and within scope.
✅ Featured Paths: PMP, PRINCE2, Microsoft Project
Empower Teams. Embrace Agility.
Elevate your workflow with Agile and Scrum training tailored for today’s fast-paced environments. Master sprint planning, backlog management, and Agile leadership.
✅ Popular Roles: Scrum Master, Product Owner
Build, Scale, and Innovate in the Cloud
Gain hands-on experience with cloud platforms and DevOps pipelines. Learn to deploy, manage, and automate infrastructure using AWS, Azure, Docker, Jenkins, and more.
✅ Key Platforms: AWS, Azure, Google Cloud, Docker, Jenkins
Design Smarter IT Systems
Streamline IT operations using frameworks like ITIL® and TOGAF®. Align IT services with business strategy while architecting scalable, resilient systems.
✅ Certifications Offered: ITIL®, TOGAF®, COBIT
Drive Excellence. Ensure Consistency.
Master Six Sigma, Lean, and TQM to lead process improvements, reduce defects, and enhance customer satisfaction. Build a culture of operational excellence.
✅ Popular Roles: Quality Analyst, Six Sigma Expert
Code Smarter. Build Faster.
From full-stack to front-end, gain expertise in modern programming languages and frameworks to build robust, scalable applications.
✅ Popular Roles: Full Stack Developer, Software Engineer
Shape Tomorrow with Smart Tech
Master generative AI models, neural networks, and ML algorithms to create intelligent, adaptive solutions. Learn practical applications in NLP, image generation, and predictive analytics.
✅ Popular Roles: AI Engineer, ML Specialist
Turn Numbers into Strategic Decisions
Learn to analyze trends, visualize data, and use predictive modeling tools like Python, R, and SQL to make business-critical decisions.
✅ Popular Roles: Data Scientist, Business Analyst
Market Smarter in a Digital World
Learn SEO, social media marketing, email campaigns, performance analytics, and more. Master the tools that power digital marketing success.
✅ Key Skills: Google Ads, Analytics, SEO, Content Strategy
Master Numbers, Drive Strategy
Build expertise in accounting principles, financial analysis, budgeting, and reporting. Ideal for finance professionals and aspiring CPAs.
✅ Popular Topics: Financial Planning, IFRS, Cost Management
This course brings together several key information technologies used in manipulating, storing, and analyzing big data. We look at the basic tools for statistical analysis, R, and key methods used in machine learning. We review MapReduce techniques for parallel processing and Hadoop, an open source framework that allow us to cheaply and efficiently implement MapReduce on Internet scale problems. We touch on related tools that provide SQL-like access to unstructured data: Pig and Hive. We analyze so-called NoSQL storage solutions exemplified by HBase for their critical features: speed of reads and writes, data consistency, and ability to scale to extreme volumes. We examine memory resident databases and streaming technologies which allow analysis of data in real time. We work with the public cloud as unlimited resource for big data analytics. Students gain the ability to design highly scalable systems that can accept, store, and analyze large volumes of unstructured data in batch mode and/or real time
<ul class="tabbed-list"> <li>What is BigData</li> <li>Hadoop Overview</li> <li>Introduction to HDFS</li> <li>HDFS Architecture</li> <li>MapReduce v1</li> <li>MapReduce v2/YARN</li> <li>HBase</li> <li>Hive</li> <li>Pig</li> <li>Flume</li> <li>Sqoop</li> </ul> <p> </p> <p>This course brings together several key information technologies used in manipulating, storing, and analyzing big data. We look at the basic tools for statistical analysis, R, and key methods used in machine learning. We review MapReduce techniques for parallel processing and Hadoop, an open source framework that allow us to cheaply and efficiently implement MapReduce on Internet scale problems. We touch on related tools that provide SQL-like access to unstructured data: Pig and Hive. We analyze so-called NoSQL storage solutions exemplified by HBase for their critical features: speed of reads and writes, data consistency, and ability to scale to extreme volumes. We examine memory resident databases and streaming technologies which allow analysis of data in real time. We work with the public cloud as unlimited resource for big data analytics. Students gain the ability to design highly scalable systems that can accept, store, and analyze large volumes of unstructured data in batch mode and/or real time</p>