Professional Diploma in Data Science and Artificial Intelligence

The module “Business Analytics" is designed to empower learners with the essential knowledge and skills required to thrive in the dynamic field of data analysis. Through a structured series of learning units, participants will establish a robust foundation in various facets of data analytics. The module commences with an exploration of fundamental concepts in data analytics and Power BI, enabling participants to adeptly prepare and transform data, create insightful visualizations and reports, develop data models, and proficiently format and present information using interactive dashboards.

Expanding on the expertise garnered from the learning units, participants will engage in hands-on, real-world scenarios through a comprehensive project. This project offers a unique opportunity to implement a data analytics solution employing Power BI. By leveraging Power BI, participants will gain practical experience in analyzing and interpreting data and making informed decisions based on data insights. This practical application will foster the development of the participant"s capacity to extract meaningful insights, collaborate effectively, and actively contribute to the success of businesses.

Upon successful completion of the “Business Analytics" module, participants will emerge with a profound understanding of data analytics principles and techniques. They will possess proficiency in utilizing Power BI, equipped with the necessary skills to prepare and transform data, craft impactful visualizations and reports, develop data models, and design interactive dashboards. Furthermore, participants will be empowered to apply their acquired knowledge in practical settings, utilizing data analysis to drive informed decision-making and address intricate business challenges.

In the "Generative AI" module, learners will learn about different AI models and how they're used in real life. We'll start with the basics of these AI models, understanding how they work. We'll also explore practical tools like ChatGPT, Copilot, and Power Virtual Agents from Microsoft. By using these tools, learner will discover how Generative AI can be applied in various ways, like research and creating content.

In this module, learners will explore the practical applications of ChatGPT and Microsoft 365 Copilot. They'll uncover how ChatGPT is used in real life, such as in research, creating content, boosting business productivity, and assisting with customer support. Through hands-on experiences, participants will learn how to use AI tools like ChatGPT and Microsoft Copilot to craft engaging and interactive content. Furthermore, the module will equip learners with the skills to create functional ChatBots using Microsoft Power Virtual Agents and Copilot, facilitating smooth interactions with users.

By the end of this module, participants will have a solid grasp of AI models, as well as practical expertise in effectively utilizing ChatGPT, Copilot, and Microsoft Power VA for tasks like content creation, multimedia presentations, improving business productivity, and enhancing customer support. 

Embark on a transformative journey into the realm of app development with our "Robotic Process Automation" module. This comprehensive program equips learners with the skills needed to thrive in the dynamic landscape of low-code development, turning them into tech practitioners in their specific job functions. Graduates can seamlessly transition into roles such as Low-Code Developer, Power Platform Developer, or even carve a niche as an HR Tech Practitioner, where they will be sought after for their ability to streamline HR processes, automate workflows, and create robust applications with efficiency. The module not only hones technical prowess but also nurtures a deep understanding of the business value inherent in low-code solutions, making our graduates indispensable assets in the ever-evolving tech industry.

Delving into the heart of the module, learners first grasp the fundamental "Business value of Power Platform," gaining insights into the strategic advantages and transformative potential of low-code solutions. This foundational knowledge sets the stage for the subsequent exploration of "Power Automate Core Components," where students unravel the intricacies of this powerful tool for automating workflows. The focus then shifts to "Dynamic Decision-Making in Power Automate Workflows," providing learners with the skills to create responsive and adaptive workflows that dynamically respond to changing conditions, enhancing the overall efficacy of their applications.

Moving forward, the module navigates through "Unlocking Power Automate Potential with Excel and Document Generation," imparting expertise in leveraging Excel and document generation to unleash the full potential of Power Automate. This module empowers learners to harness the capabilities of these ubiquitous tools, expanding the scope and functionality of their applications. "Data Modelling and Model-Driven App" is the next frontier, where participants delve into the intricacies of data modeling and learn to craft model-driven applications. This unit not only solidifies their grasp on the theoretical underpinnings but also instils practical skills for building apps that are not only user-friendly but also tailored to specific business needs.

As the module progresses, learners venture into the realm of "Canvas App," where they master the art of creating visually engaging and interactive applications. This unit provides hands-on experience in designing apps with a focus on user interfaces and user experiences, ensuring graduates can deliver solutions that are not just functional but also aesthetically pleasing. Each instructional unit serves as a steppingstone, building a robust skill set that enhances their current skillset, opening doors to new job opportunities and allowing them to contribute meaningfully to the success of any organization in today's fast-paced, technology-driven world.

In the "Capstone Project-Business Analytics" module, learners will immerse themselves in a comprehensive learning experience, acquiring knowledge and skills essential for proficient data analytics and AI applications. The module incorporates both asynchronous and synchronous sessions, guiding learners through the intricacies of project management, data acquisition, and the preparation and transformation of data. These sessions emphasize statistical analysis and modelling using powerful tools like Power BI for data analytics and generative AI for advanced insights. Throughout this multifaceted journey, learners gain expertise in designing and architecting projects, identifying and addressing business problems, and developing interactive dashboards and reports.

The practical application of knowledge is a cornerstone of this module, realized through engaging projects that mirror real-world scenarios. Learners will undertake projects such as developing Canvas Apps for employee milestone feedback using PowerApps Forms, refining chatbot design flows, and implementing business process automation with the Power Platform. These projects serve as a bridge between theoretical understanding and practical implementation, allowing learners to integrate and apply their acquired skills. By delving into these projects, participants not only master individual components but also gain a holistic perspective, preparing them to navigate the complexities of actual data analytics and AI projects successfully.

Upon completing this module, learners will emerge with a unique set of abilities, able to lead and execute end-to-end data analytics and AI projects. From meticulous project planning and data preparation to crafting insightful visualizations and implementing sophisticated automation, graduates will be well-equipped to tackle the challenges of the evolving landscape in data science and artificial intelligence. This module, with its blend of theoretical foundations and hands-on projects, ensures that learners are not just knowledgeable but also possess the practical skills necessary for making a meaningful impact in the field.

The "Data Science essentials" module equips learners with essential knowledge and skills crucial for navigating the data-driven landscape. Covering a spectrum of topics, including Fundamentals of Python, Data processing using Python, Introduction to Machine Learning, and Automated Machine Learning, this module lays a robust foundation for aspiring data scientists.

Through hands-on projects, learners will apply theoretical concepts to real-world scenarios. The module kicks off with the fundamentals of Python syntax, data types, functions, conditional statements, and Pandas data processing. The learners will get insights about the fundamentals of data and data storage. They will be familiarized with the implementation of machine learning tasks with AutoML providing practical insights into machine learning. This hands-on experience reinforces the understanding of how automation can streamline complex machine-learning processes.

The culmination involves an exploration of various machine learning algorithms within the AutoML framework, followed by a comparative study of the models generated. This project not only sharpens technical proficiency but also cultivates the ability to assess and select optimal models for different scenarios. By the module's conclusion, learners will emerge with a comprehensive skill set encompassing data fundamentals, AI principles, pre-processing techniques, and practical experience in developing automated machine learning solutions.

The "Applied Machine Learning" module empowers learners with a profound understanding of key concepts and practical skills required in real-world applications. Through a structured curriculum, participants delve into Regression tasks, Classification tasks, and Clustering tasks, and harness the power of Azure AI Services for Pre-built models, culminating in a focus on Text Analysis with the Language Service.

Learners master the intricacies of Regression tasks, acquiring the ability to select and apply appropriate algorithms for predictive modelling. The module extends to Classification tasks, providing insights into classifying data into distinct categories, and delves into Clustering tasks, unravelling techniques to group data points based on inherent patterns. Additionally, participants gain proficiency in leveraging Azure AI Services for Pre-built models, enhancing their toolkit with readily available models for diverse applications. The module concludes with a deep dive into Text Analysis using the Language Service, unravelling the complexities of processing, and extracting insights from textual data.

Through hands-on projects, participants implement machine learning tasks using Azure ML Designer, facilitating a comparative analysis of algorithmic performance. The culmination involves the implementation of regression, classification and clustering using Azure ML Studio. As a result, learners emerge with a robust skill set, ready to apply machine learning principles to solve complex problems in diverse domains.

The "Deep Learning" module provides learners with a comprehensive understanding of key concepts and skills in the realm of deep learning. Covering crucial learning units including Introduction to Computer Vision, Face Recognition and Optical Character Recognition, Image Classification, Introduction to Natural Language Processing, and Conversational Language Understanding, this module offers a robust foundation for those seeking to apply deep learning techniques in practical scenarios.

Through hands-on projects, participants will translate theoretical knowledge into tangible skills. The module commences with the implementation of Optical Character Recognition using the Azure AI Vision portal, allowing learners to gain practical insights into extracting and processing text from images. Subsequently, participants delve into the realm of text analysis using the Azure Language portal, showcasing the application of deep learning in extracting meaningful information from textual data.

By the conclusion of the module, learners will have honed their abilities in computer vision, image classification, and natural language processing. The practical projects not only reinforce technical skills but also instil a proficiency in leveraging deep learning tools for real-world applications, empowering participants to engage in face recognition, text extraction, and analysis tasks using state-of-the-art technologies.

The "Capstone Project - Data Analytics module serves as a pivotal opportunity for students enrolled in the "Professional Diploma in Data Science & Artificial Intelligence" to apply the knowledge and skills acquired in preceding course modules. The Capstone Project module extends this foundation, enabling students to refine their practical skills by engaging in real-world projects and addressing industry challenges.

This module immerses learners in the day-to-day operations of live industry projects, allowing them to apply technical skills in data analysis, machine learning model development, and the utilization of deep learning techniques. Through hands-on experience with industry-standard tools, collaboration with professionals, and project management, students gain a comprehensive understanding of the data science lifecycle. The practical experience obtained not only enhances technical proficiency but also cultivates critical thinking, problem-solving, and communication skills within a professional context.

Ultimately, the Capstone Project module positions students as well-rounded data science and AI professionals, providing a competitive edge in the job market. Bridging the gap between theory and practice, learners showcase their ability to solve real-world problems and deliver tangible results. The acquired hands-on experience establishes a robust foundation for future careers, enabling graduates to contribute effectively to the industry and make a positive impact in the dynamic field of data science and AI.