The Ultimate 70+ Hours iOS Development Bootcamp

Please Note: This course contains the use of artificial intelligence.Modern workplaces move fast, and teams depend on leaders who can guide them with confidence, clarity, and purpose. When leaders lack strong Management Skills and Team Leadership abilities, teams lose focus, communication breaks down, and progress slows. This masterclass gives you the complete toolkit you need to lead people effectively, motivate diverse teams, and create a confident leadership presence.You start by learning core foundations of team leadership, including the behaviors that build trust, strengthen relationships, and support team growth. You also learn clear communication techniques that help you influence decisions, negotiate confidently, and resolve workplace conflict in a calm, structured way.The course teaches you how team dynamics shape performance and how motivation and inclusion improve collaboration. You will explore people and talent systems, performance management, structured feedback, and development planning—all key abilities for leaders who want long-term team success.You will also learn the essentials of goals, metrics, and data-driven decisions. This helps you set clear targets, evaluate progress, and lead teams with transparency and accountability. The project leadership modules show you how to plan work, manage timelines, coordinate tasks, and guide your team through ongoing responsibilities.Finally, you develop key abilities for leading change and driving resilience. You learn how to guide teams through uncertainty, encourage innovation, and keep people motivated even during demanding periods. With these skills, you stand out as a confident, positive, and forward-thinking leader ready for higher responsibility.Learning OutcomesAfter completing this course, you will be able to:Strengthen core Management Skills for confident team direction and decision support.Communicate with clarity to influence decisions, g

This course is designed for busy professionals who want to use AI in a serious, structured way in their work—not just experiment with it once and forget about it.In AI Crash Course for Professionals: Gen-AI for Everyday Work, you will move from knowing almost nothing about AI to using it confidently and consistently in your daily tasks. The course is fully practical and non-technical: clear explanations, step-by-step demonstrations, and real workplace examples.You will work with a toolbox of AI assistants, including:ChatGPT for writing, editing, and structured thinkingPerplexity for research, fact-checking, and document summarizingMicrosoft Copilot / Google Gemini as examples of integrated workplace AIGamma for creating and improving presentations and slide decksFathom for recording, summarizing, and following up on meetingsPlus other helpful tools such as Notion AI where relevantYou will learn how to:Turn rough ideas into clear, professional emails, reports, and proposalsPrepare presentations faster and with more structure using AI toolsUse AI to research topics, compare options, and digest long documentsCapture meetings and turn them into action points and follow-up plansBuild simple, repeatable AI workflows that you can use every dayWe also address professional and ethical use of AI at work: privacy, confidentiality, bias, and how to keep human judgment and values at the center.By the end of the course, you will have a personal AI toolkit and routine that help you save time, reduce stress, and deliver higher-quality work in a consistent way.No coding or techn

In this course, you will begin by setting up your Python and VS Code development environment. We will then introduce the LangChain Framework, which is a powerful tool for building AI applications. You will also learn about obtaining an OpenAI API Key.Throughout the course, we will guide you in developing a Python application that can read YouTube video transcripts using the pytube library. We will demonstrate how to create a Vector Database from these transcripts using LangChain. Additionally, you will learn how to query the Vector Database using the OpenAI API.Furthermore, we will introduce you to Excalidraw, a versatile tool for creating visual illustrations. App with elegant look and feel will be developed using Python streamlit. Separate lectures are provided on how to install and run streamlit apps.Finally, we will guide you in deploying your application using a cloud hosting service, ensuring that it is accessible through a web-based user interface.By the end of this course, you will have gained the necessary skills to build a sophisticated Python app that can process YouTube video transcripts, utilize AI capabilities through the OpenAI API, and present the results through an intuitive web interface.Complete source code will be shared with you on GitHub.

Object Detection IntroOne of the important fields of Artificial Intelligence is Computer Vision. Computer Vision is the science of computers and software systems that can recognise and understand images and scenes. Computer Vision is also composed of various aspects such as image recognition, object detection, image generation, image super-resolution and more. Object detection is probably the most profound aspect of computer vision due the number practical use cases. In this tutorial, I will briefly introduce the concept of modern object detection, challenges faced by software developers, the solution my team has provided as well as code tutorials to perform high performance object detection.Object detection refers to the capability of computer and software systems to locate objects in an image/scene and identify each object. Object detection has been widely used for face detection, vehicle detection, pedestrian counting, web images, security systems and driverless cars. There are many ways object detection can be used as well in many fields of practice. Like every other computer technology, a wide range of creative and amazing uses of object detection will definitely come from the efforts of computer programmers and software developers.CourseLearn to create Machine Learning Model within an hour with minimal coding and no math involved. We will be using the Google Teachable machine and exploring different test cases for object detection.

This course is designed for developers and IT professionals who want to get started with Microservices Architecture and understand how modern distributed systems are designed and structured. It provides a clear, conceptual foundation for learners who are new to microservices and want to understand why and how microservices are used in real‑world applications.The course begins with the basics of Microservices Architecture, explaining what microservices are and how they differ from traditional application architectures. You will gain a clear understanding of microservices characteristics, including scalability, independence, and decentralized development.You will then explore architectural comparisons such as SOA vs Microservices and Monolithic vs Microservices architecture, helping you understand the evolution of application design and the trade‑offs involved in each approach.Communication between services is a critical aspect of microservices, so the course covers microservices communication patterns and explains how services interact with each other. You will also learn about the role of an API Gateway and how it acts as a single entry point for client requests.The course further introduces service discovery and explains how microservices locate and communicate with each other dynamically. Popular components such as Netflix Eureka are discussed to help you understand real‑world implementations. Advanced concepts such as the Circuit Breaker pattern and Distributed Tracing are also covered, including an introduction to Zipkin, to help you understand system resilience and observability in distributed environments.Practice tests are included to reinforce learning and validate your understanding of microservices concepts.

Welcome to the course Master Regression and Feedforward Networks!This course will teach you to master Regression, Regression analysis, and Prediction with a large number of advanced Regression techniques for purposes of Prediction and Machine Learning Automatic Model Creation, so-called true machine intelligence or AI.You will learn to handle advanced model structures and eXtreme Gradient Boosting Regression for prediction tasks. You will learn modeling theory and several useful ways to prepare a dataset for Data Analysis with Regression Models.You will learn to:Master Regression, Regression analysis, and Prediction both in theory and practiceMaster Regression models from simple linear Regression models to Polynomial Multiple Regression models and advanced Multivariate Polynomial Multiple Regression models plus XGBoost RegressionUse Machine Learning Automatic Model Creation and Feature SelectionUse Regularization of Regression models and to regularize regression models with Lasso and Ridge RegressionUse Decision Tree, Random Forest, XGBoost, and Voting Regression modelsUse Feedforward Multilayer Networks and Advanced Regression model StructuresUse effective advanced Residual analysis and tools to judge models’ goodness-of-fit plus residual distributions.Use the Statsmodels and Scikit-learn libraries for Regression supported by Matplotlib, Seaborn, Pandas, and PythonCloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources.Option: To use the Anaconda Distribution (for Windows, Mac, Linux)Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages – golden nuggets to improve your quality of work