- Learn how to design, build and deploy large-scale big data systems for complex enterprise architectures.
- Understand various distributed processing frameworks and engine main with Apache Spark, Hadoop, Apache Flink, and their use-cases.
- Learn how to migrate traditional data processing workloads to cloud-based big data services with AWS, Google Cloud, and Microsoft Azure.
- Gain practical skills in architecting and configuring big data systems on cloud platforms as well as on-premise infrastructures.
- Learn how to design data warehouse solutions and understand different ETL techniques.
- Develop hands-on experience in implementing data lakes, warehouses, and data marts.
- Understand data governance, security, and privacy best practices in big data systems.
- Learn how to implement end-to-end workflows across batch processing, stream processing, and machine learning using stack Apache Spark, Apache Flink, and TensorFlow.
- Develop hands-on skills in integrating heterogeneous systems including communication with restful APIs, file transfers, message queues, and publish/subscribe mechanisms.
- Gain practical experience in implementing deep learning techniques for real-world problems, including natural language processing, image, and voice recognition.
Course Title: Certified Senior Big Data Engineer Proficiency Level: Advanced Prerequisite Requirements: Certification as a Big Data Engineer or equivalent work experience of at least 3 years. Course Description: Unit 1: Introduction to Big Data Architecture and Design Unit 2: Analyzing Large-Scale Data with Apache Spark Unit 3: Distributed Data Science and Engineering Using Spark Unit 4: Migrating Data Processing Workloads to Cloud Unit 5: Big Data Implementation on AWS Unit 6: Architecting Big Data Solutions with Google Cloud Unit 7: Designing and Implementing Big Data on Microsoft Azure Unit 8: Data Warehouse Architecture and Design Unit 9: Implementing Data Lakes and Data Warehouses Unit 10: Big Data Governance and Security Unit 11: Data Pipeline and Workflow Orchestration Unit 12: Integrating Big Data with Enterprise Systems Unit 13: Machine Learning for Big Data Unit 14: Applying Deep Learning Techniques on Big Data Unit 15: Distributed Data Processing with Apache Flink Unit 16: Capstone Project Course Objectives:
Course Title: Certified Supply Chain Professional Course Description: The course is designed to help learners develop practical skills required for an intermediate Certified Supply Chain Professional in a modern business environment. The course focuses on industry-wide standards and best practices. All objectives are measurable, and learners are equipped with the knowledge and skills needed for a successful career in supply chain management. Course Structure: Unit 1: Introduction to Supply Chain Management Unit 2: Demand Management Unit 3: Advanced Forecasting Techniques Unit 4: Inventory Management Unit 5: Distribution and Transportation Management Unit 6: Warehouse Management Unit 7: Procurement and Purchasing Unit 8: Supplier Management Unit 9: Lean Supply Chain Management Unit 10: Sustainability in Supply Chain Management Unit 11: Project Management in Supply Chain Unit 12: Capstone Project Course Objectives:- Understand the fundamental concepts of supply chain management
- Learn how to manage demand and forecast future sales and production needs
- Understand the fundamentals of efficient inventory management and control processes
- Develop practical skills in distribution and transportation management, including route optimization, network design, and shipment tracking
- Develop skills in warehouse management and optimization, including layout design, inventory tracking, and labor management
- Gain an understanding of procurement and purchasing, including supply market analysis, supplier evaluation, and vendor selection
- Learn how to develop and maintain strong relationships with suppliers and ensure that they meet quality, delivery, and cost requirements
- Gain practical experience in lean supply chain management, including value stream mapping, continuous improvement, and defect reduction
- Understand the importance of sustainability and ethical considerations in supply chain management and identify the potential social and environmental impacts of supply chain operations
Course Title: Certified in Production and Inventory Management Course Length: 10 Units Proficiency Level: Intermediate Prerequisite Requirements: None Course Description: The course is designed to help learners develop practical skills required for an Intermediate Certified in Production and Inventory Management in a modern business environment. The course focuses on industry-wide standards and best practices. All objectives are measurable, and learners are equipped with the knowledge and skills needed for a successful career in production and inventory management. Course Structure: Unit 1: Introduction to Production and Inventory Management Unit 2: Demand Management Unit 3: Master Production Scheduling Unit 4: Material Requirements Planning Unit 5: Capacity Planning Unit 6: Production Activity Control Unit 7: Inventory Fundamentals Unit 8: Inventory Systems and Models Unit 9: Lean Production and Inventory Management Unit 10: Capstone Project Course Objectives:- Understand the basic concepts of production and inventory management.
- Learn how to manage customer demand and forecast future sales.
- Understand the concepts of master production scheduling and its role in production planning.
- Learn how to use material requirements planning (MRP) to optimize inventory levels.
- Develop capacity planning skills to ensure efficient use of resources and maximize productivity.
- Learn how to use production activity control (PAC) techniques to manage production schedules and ensure on-time delivery.
- Understand inventory fundamentals, including inventory costs, service levels, and order quantities.
- Develop knowledge in inventory systems and models, including economic order quantity (EOQ), safety stock, and reorder point.
- Develop skills in lean production and inventory management, including process improvement, waste reduction, and continuous improvement.
- Apply the knowledge and skills gained in the course to a capstone project that simulates real-world production and inventory management scenarios.
Course Title: Certified in Logistics, Transportation, and Distribution Course Length: 16 Units Proficiency Level: Advanced Prerequisite Requirements: Participants seeking to enroll in the Certified in Logistics, Transportation, and Distribution (Advanced Level) certification must have completed the "Certified Logistics Professional" or an equivalent course to ensure they have foundational knowledge in logistics and supply chain management.. Course Structure: Unit 1: Introduction to Advanced Logistics Management Unit 2: Logistics Strategy and Planning Unit 3: Freight Transportation Modes and Analysis Unit 4: Advanced Inventory Management Techniques Unit 5: Warehouse Operations and Automation Unit 6: Transportation Network Design and Optimization Unit 7: Global Supply Chain Management Unit 8: Risk Management in Logistics and Transportation Unit 9: Sustainable Practices in Supply Chain Unit 10: Technology Integration in Logistics Unit 11: E-commerce and Last-Mile Delivery Solutions Unit 12: Reverse Logistics and After-Sales Support Unit 13: Regulatory Compliance in Transportation Unit 14: Project Management in Logistics Unit 15: Data Analytics for Decision Making Unit 16: Future Trends in Logistics and Distribution Course Objectives:- Develop comprehensive logistics strategies that align with organizational goals and objectives.
- Analyze and optimize transportation modes to reduce costs and improve efficiency.
- Implement advanced inventory management techniques to ensure optimal stock levels.
- Utilize warehouse automation to enhance operational productivity and accuracy.
- Design and optimize transportation networks for seamless distribution.
- Understand the complexities of managing global supply chains and implementing effective international logistics solutions.
- Identify potential risks in logistics operations and implement risk management strategies.
- Promote sustainability practices within the supply chain for environmental and social responsibility.
- Integrate technology solutions to streamline logistics processes and improve visibility.
- Implement effective e-commerce and last-mile delivery solutions to meet customer expectations.
- Manage reverse logistics and after-sales support efficiently to enhance customer satisfaction.
- Ensure compliance with transportation regulations and legal requirements.
- Apply project management principles to execute logistics initiatives successfully.
- Use data analytics to make data-driven decisions and optimize logistics operations.
- Stay informed about emerging trends and innovations in logistics and distribution.
Course Title: Certified Senior Big Data Analyst Proficiency Level: Advanced Prerequisite Requirements: Prior knowledge in basic data analytics and big data technologies required. Completion of "Certified Big Data Analyst" or equivalent recommended. Course Description: Unit 1: Introduction to Advanced Big Data Analytics Unit 2: Big Data Technologies and Ecosystem Unit 3: Data Acquisition and Integration Unit 4: Data Preprocessing and Cleaning Unit 5: Exploratory Data Analysis (EDA) in Big Data Unit 6: Advanced Data Visualization Techniques Unit 7: Machine Learning for Big Data Analysis Unit 8: Deep Learning and Neural Networks Unit 9: Natural Language Processing (NLP) in Big Data Unit 10: Sentiment Analysis and Text Mining Unit 11: Big Data for Business Intelligence Unit 12: Predictive Analytics and Modeling Unit 13: Time Series Analysis in Big Data Unit 14: Anomaly Detection and Fraud Analytics Unit 15: Big Data Security and Privacy Unit 16: Big Data Ethics and Governance Course Objectives:- Understand the principles and significance of advanced big data analytics in various industries.
- Familiarize themselves with the latest big data technologies and tools within the big data ecosystem.
- Acquire, clean, and integrate diverse data sources to create a unified data repository.
- Perform exploratory data analysis (EDA) to gain insights and identify patterns in big data.
- Utilize advanced data visualization techniques to effectively communicate complex findings.
- Apply machine learning algorithms to big data for predictive modeling and pattern recognition.
- Explore deep learning and neural networks to analyze unstructured data and perform image and speech recognition tasks.
- Employ natural language processing (NLP) techniques to extract valuable information from text data.
- Conduct sentiment analysis and text mining to understand customer sentiments and opinions.
- Leverage big data for business intelligence and data-driven decision-making.
- Build predictive models to forecast future trends and outcomes using big data.
- Analyze time series data for trend analysis and forecasting in big data scenarios.
- Identify anomalies and detect fraud using advanced analytics on big data.
- Implement security measures and privacy protection techniques for big data environments.
- Understand the ethical implications of big data analytics and govern data usage responsibly.
Course Description: This course covers the development and implementation of urban transport policies and plans, focusing on the role of government, stakeholders, and regulatory frameworks. Students will learn to develop policies that promote sustainable and efficient urban transport. Course Objectives:- Understand the principles of urban transport policy and planning.
- Learn about the role of government and stakeholders in transport planning.
- Develop strategies for creating sustainable urban transport policies.
- Implement regulatory frameworks for urban transport planning.
- Evaluate the impact of transport policies on urban mobility and development.
- Develop and implement effective urban transport policies.
- Engage with government and stakeholders in transport planning.
- Create strategies for sustainable urban transport policies.
- Ensure compliance with regulatory frameworks in transport planning.
- Assess the impact of transport policies on urban mobility.
Course Description: This course focuses on the planning and promotion of non-motorized transport modes, including walking and cycling. Students will learn about the benefits of non-motorized transport, infrastructure design, and strategies to encourage its use. Course Objectives:- Understand the principles of non-motorized transport planning.
- Learn about the benefits of walking and cycling in urban areas.
- Develop infrastructure plans for non-motorized transport.
- Implement strategies to promote walking and cycling.
- Evaluate the impact of non-motorized transport on urban mobility.
- Develop and implement infrastructure plans for non-motorized transport.
- Promote the benefits of walking and cycling in urban areas.
- Design safe and accessible infrastructure for non-motorized transport.
- Assess the impact of non-motorized transport on urban mobility.
- Increase the use of walking and cycling through targeted strategies.
Course Description: This course explores transport demand management (TDM) strategies to reduce congestion and improve urban mobility. Students will learn about TDM techniques, policy measures, and the implementation of demand management programs. Course Objectives:- Understand the principles of transport demand management.
- Learn about TDM techniques and policy measures.
- Develop strategies to reduce transport demand and congestion.
- Implement demand management programs in urban areas.
- Evaluate the impact of TDM on urban mobility and accessibility.
- Develop and implement effective transport demand management strategies.
- Reduce congestion through targeted TDM measures.
- Implement demand management programs in urban areas.
- Assess the impact of TDM on urban mobility and accessibility.
- Improve urban transport efficiency through demand management.
Course Description: This course covers safety and security measures in public transport systems, including risk management, incident response, and the development of safety protocols. Students will learn to enhance the safety and security of public transport services. Course Objectives:- Understand the principles of public transport safety and security.
- Learn about risk management and incident response in public transport.
- Develop safety protocols for public transport systems.
- Implement security measures to protect public transport assets.
- Evaluate the impact of safety and security measures on public transport.
- Develop and implement safety protocols for public transport systems.
- Manage risks and respond to incidents effectively.
- Enhance security measures for public transport services.
- Assess the impact of safety and security measures on public transport.
- Improve the safety and security of public transport through targeted strategies.
Course Description: This course focuses on the management of urban traffic flow, including congestion management, traffic signal optimization, and the use of intelligent transport systems (ITS). Students will learn to develop and implement traffic flow management plans. Course Objectives:- Understand the principles of urban traffic flow management.
- Learn about congestion management and traffic signal optimization.
- Develop strategies to improve urban traffic flow.
- Implement intelligent transport systems for traffic flow management.
- Evaluate the impact of traffic flow management on urban mobility.
- Develop and implement effective urban traffic flow management plans.
- Optimize traffic signals to improve traffic flow.
- Reduce congestion through targeted management strategies.
- Utilize intelligent transport systems for traffic flow management.
- Assess the impact of traffic flow management on urban mobility.