Courses

Learn how to manage your manager. In this course, adapted from the podcast How to Be Awesome at Your Job, Mary Abbajay explains how to build a good relationship with your boss.

Learn how to create and manage apps with SCCM and prepare for Microsoft certification exam 70-703. See how to deploy apps using PowerShell scripts, and deploy App-V virtual apps.

Great leadership doesn't happen by chance—it happens by design. This course helps you create and evolve a personalized leadership checklist that keeps you focused on what matters most. You'll learn the core components of an effective checklist, from daily practices to strategic responsibilities, and how to structure them for clarity and action. Through practical tools, case examples, and hands-on activities, you'll build a Version 1 of your leadership checklist, test it against real challenges, and refine it as your role evolves.

Looking for a consistent and reliable way to install Windows applications? Learn about the Chocolatey package manager.

This course focuses on understanding why managers are crucial to team success and the positive impact they can have. It covers recognizing both effective and ineffective management behaviors and highlights the unique value managers bring to their teams.

Learn how to transition from individual contributor to Manager and Leader with confidence! What you'll learn: Welcome to your career in management. But most important…Welcome to leadership. Even for the most gifted individuals, the process of becoming a leader is a rigorous and many times an exhausting journey. The rewards, however, can be enormous. I surveyed a group of managers across many disciplines and asked the question, “As a new manager, what do you wish you learned early in your career?” What follows in this course, is a result of the responses, as well as my personal experience coaching and mentoring new managers. I will open this course by asking you to be patient with yourself. You do not develop leadership skills overnight. It takes practice, it takes trying new things, it takes making mistakes. Yes, sometimes you will fail. That is ok. It is ok to acknowledge when something doesn’t work, it is ok to celebrate and build on your successes. I have broken this course into individual modules. These are small bite sized modules that you can view either one after the other, or one at a time as you drink your morning coffee. Feel free to jump around and view the modules that are of the most importance to you. Take what works, challenge what doesn’t, try new things. I’m excited to join you in this journey. It’s time to think about success. Let’s Get Started. Welcome to your career in management. But most important…Welcome to leadership. Why did you make this big move? To grow personally and professionally? To make a difference? To lead others to realize their success? All of the above?All this, and more! Even for the most gifted individuals, the process of becoming a leader is a rigorous and many times an exhausting journey. The rewards, however, can be enormous. I surveyed a group of managers across many disciplines and asked the question, “As a new manager, what do you wish you learned early in your career?” What follows in this course, is a result of the responses, as well as my personal experience coaching and mentoring new managers. I will begin by asking you to be patient with yourself. You do not develop leadership skills overnight. It takes practice, it takes trying new things, it takes making mistakes. Yes, sometimes you will fail. That is ok. It is ok to acknowledge when something doesn’t work, it is ok to celebrate and build on your successes. I have broken this course into individual modules. These are small bite sized modules that you can view either one after the other, or one at a time as you drink your morning coffee. Feel free to jump around and view the modules that are of the most importance to you. Take what works, challenge what doesn’t, try new things.The Chapters include:Introduction to ManagementDeveloping Your Leadership StyleLeadership ResponsibilitiesLeadership CommunicationTeam DevelopmentYour Growth and DevelopmentManagers Toolkit I’m excited to join you in this journey. It’s time to think about success. Let’s Get Started.

Learn the skills you need as a middle manager, including how to build strong hybrid teams, onboard new employees, conduct performance reviews and give feedback, develop OKRs to drive business alignment, trust your teams to do their best work, build visibility online as a remote leader, and communicate across cultures virtually. After completing this learning path, advance your skills with Manage Remote and Hybrid Teams as a Senior Manager.Build strong hybrid/remote teams.Onboard new employees effectively.Create OKRs that drive alignment, autonomy, and accountability.Communicate across cultures virtually.

Discover what it means to lead at a distance. As a new manager, learn how to run effective virtual and hybrid meetings, build a virtual team culture, communicate across cultures, whether working virtually or in person, and drive engagement, productivity, and growth. After completing this learning path, advance your skills with Manage Remote and Hybrid Teams as a Middle Manager.Discover what it means to lead at a distance.Drive engagement, productivity, and growth remotely.Run effective virtual and hybrid meetings.Communicate across cultures virtually.

As a senior manager, you're leading distributed teams remotely, in an office setting or both. In this learning path, you’ll learn how to plan for and embrace this new reality, including how to run collaborative hybrid teams, communicate across cultures and create great employee experiences, coach your people, and drive results and resolve conflict.Plan for the work-from-anywhere organization.Build a high-performance work culture.Communicate across cultures virtually.Drive results and resolve conflict.

Explore the critical transition from engineering manager to manager of managers in this 23-minute conference talk that addresses the surprising lack of guidance available for this pivotal career step. Learn from practical insights gained during a year-long journey of scaling from managing one engineering team to overseeing five teams. Discover the key similarities and differences between managing individual contributors and managing other managers, while identifying which existing strengths to leverage and where new skills need development. Examine the biggest challenges faced during this transition alongside debunking common misconceptions about the role. Gain practical tips and templates for navigating information flow within organizations, influencing decisions effectively, and understanding the evolving nature of problems and their resolution at this leadership level. Whether considering this career path, currently in transition, or working alongside senior engineering leaders, acquire actionable strategies to make this professional evolution both smooth and successful while building confidence that complex leadership challenges are indeed "figurable."

Explore Azure Monitor System Center Operations Manager (SCOM) Managed Instance in this 21-minute video tutorial. Learn about the differences between DIY SCOM and SCOM MI, customer responsibilities, Microsoft-managed aspects, connectivity options, management tooling, and supported agents. Discover supported management packs, resiliency and scaling features, enhanced agent log capture, and updating processes. Gain insights into pricing models and migration strategies from existing SCOM deployments. Dive into key topics such as connectivity, management tools, and the benefits of Microsoft-managed infrastructure to understand how SCOM MI can streamline your monitoring responsibilities while maintaining familiar SCOM functionality.

COURSE OUTLINE: Data mining is the study of algorithms for finding patterns in large data sets. It is an integral part of modern industry, where data from its operations and customers are mined for gaining business insight. It is also important in modern scientific endeavors. Data mining is an interdisciplinary topic involving, databases, machine learning and algorithms. The course will cover the fundamentals of data mining. It will explain the basic algorithms like data preprocessing, association rules, classification, clustering, sequence mining and visualization. It will also explain implementations in open-source software. Finally, case studies on industrial problems will be demonstrated.

The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp. Courses 2 - 5 of this Specialization form the lecture component of courses in the online Master of Computer Science Degree in Data Science. You can apply to the degree program either before or after you begin the Specialization.

Data mining is study of algorithms for finding patterns in large data sets. It is an integral part of modern industry, where data from its operations and customers are mined for gaining business insight. It is also important in modern scientific endeavors. Data mining is an interdisciplinary topic involving, databases, machine learning and algorithms. The course will cover the fundamentals of data mining. It will explain the basic algorithms like data preprocessing, association rules, classification, clustering, sequence mining and visualization. It will also explain implementations in open source software. Finally, case studies on industrial problems will be demonstrated.INTENDED AUDIENCE : Any engineering discipline and mathematics,Physics.PREREQUISITES :NilINDUSTRY SUPPORT : TCS,Infosys,CTS,Accenture

Watch this 10-hour tutorial on Data Mining! Simply put, data mining is used to turn raw data into meaningful information. To keep up with the ever-evolving aspects of data and its domains, data handling and analysis has become crucial to understanding the information that comes attached to it, and that is exactly why data science has come such a long way, in which data mining is considered to be one of the crucial methods to identify patterns and trends in huge datasets. Great Learning brings you this beginner-friendly tutorial on Data Mining to take you from the starting point through the finishing point of everything you need to know about this domain and getting started on the journey to master it. This video starts off with an introduction to Python, followed by understanding a variety of Python libraries. Then we look at the concepts of anomaly or outlier detection. Following this, we will understand Machine Learning in detail and cluster analysis with K-means. Finally, we look at regression analysis in data mining! This video teaches Data Mining and its key functions and concepts with a variety of demonstrations & examples to help you get started on the right foot.

Learn about how the Mining Industry is being transformed in Industry 4.0 What you'll learn: Explore what the Mining Industry is and its importanceDiscover Key Insights about the Mining Industry to understand the vital role it playsDiscover the Challenges in the Mining IndustryExplore the Opportunities for Innovation in the Mining IndustryDiscover what Industry 4.0 and the Industry 4.0 Environment isExplore what Cyber Physical Systems (CPS) are, their characteristics, their benefits and their drawbacks areExplore the Impact of Industry 4.0 on the Mining Industry Did you know that the world economy and humanity is at the verge of one of the most transformational periods in history of mankind?Welcome to the forefront of technological evolution in manufacturing and beyond – welcome to the 'Mining 4.0 - The Impact of Industry 4.0 on the Mining Industry' course! In an era marked by unprecedented advancements in digitalization, connectivity, and automation, Industry 4.0 represents a paradigm shift that is reshaping the way we conceive, design, and operate industrial systems.Industry 4.0, often referred to as the fourth industrial revolution, is characterized by the integration of smart technologies, data-driven decision-making, and the seamless interconnection of machines and processes. This course is designed to be your gateway into this transformative landscape, providing a comprehensive exploration of the principles, technologies, and applications that define Industry 4.0. A course with a simple and comprehensive beginner's guide to 'Mining 4.0 - The Mining Industry in Industry 4.0'! In this course, there are TEN sections which cover over 50 lectures worth over 4 hours of content;Section 1 - Introduction to the Mining Industry - Discover what the Mining Industry is and the vital role it plays in shaping Society. Section 2 - The Key Insights in the Mining Industry - Explore the key insights about the Mining Industry such as the Supply Chain Agility, Future of Work, Increasing Demand of Rare Earth Elements (REE), etc. Section 3 - Introduction to Challenges of the Mining Sector - Explore the challenges faced by the Mining Industry such as volatility of the commodity market, access to energy, health and safety regulations, sustainability concerns, access to venture capital and the geopolitics of mining.Section 4 - Opportunities for Innovation in the Mining Industry - Discover the opportunities for innovation in the Mining Industry including Improving and Optimizing Business Operations, Improving Health and Safety of Mining, Sustainability and Eco-Friendly, Supply Chain Agility and Better Access to Energy. Section 5 - Introduction to Industry 4.0 - Discover what Industry 4.0 is, what the Industry 4.0 Environment is and the different kinds of Internets such as the Internet-of-Things (IoT), Industrial-Internet-of-Things (IIoT), Internet-of-Services (IoS) and the Internet-of-Everything (IoE) Section 6 - Introduction to Cyber Physical Systems (CPS) - Discover what Industry 4.0 is, what the Industry 4.0 Environment is and the different kinds of Internets such as the Internet-of-Things (IoT), Industrial-Internet-of-Things (IIoT), Internet-of-Services (IoS) and the Internet-of-Everything (IoE). Section 7 - The Impact of Industry 4.0 on Mining Industry - Discover how Industry 4.0 is impacting and transforming the Mining Industry including Total Visibility of the Value Chain, Applications of Augmented Reality (AR), Virtual Reality (VR) and Mixed Reality (MR), Proactive Maintenance of Resources, Additive Manufacturing (3D Printing) and Remote Monitoring of Resources. Section 8 - Innovative Startups and Businesses of the Mining Industry - Discover Innovative Startups and Businesses in the Mining Industry. Section 9 - The Barriers to Implementing Industry 4.0 - Discover about the barriers of implementing Industry 4.0 including the high cost of implementation, lack of skilled staff, privacy issues and concerns. Section 10 - The Drivers of Implementing Industry 4.0 - Discover about the Barriers of Implementing Industry 4.0 including Faster Time to Market, Challenges in matching the Supply and Demand, Better Customer Experience (CX), Increasing efficiency and productivity in business processes and Demand for Better Quality. Jump right in to learn and discover about all of the amazing and transformative content on Mining 4.0 - The Mining Industry in Industry 4.0 and be updated with latest trends in the world of tech and business! Be a part of Industry 4.0! Disclaimer #1: This course includes case studies of various companies to illustrate the real-world applications of Industry 4.0 and digital transformation. The case studies are based on publicly available information, industry trends, and analysis for educational purposes only.The inclusion of specific companies does not imply any endorsement, affiliation, or sponsorship. Likewise, any insights, opinions, or conclusions drawn from these case studies are those of the course creator and should not be interpreted as official statements from the companies mentioned. This course is not affiliated with, endorsed by, or sponsored by any of the companies mentioned. All company names, trademarks, and registered trademarks are the property of their respective owners.While every effort has been made to ensure accuracy, the rapidly evolving nature of technology means that some information may become outdated or incorrect. Participants are encouraged to conduct their own research and verify details independently. If such information is found, kindly inform us to rectify outdated/incorrect information at the earliest.This course is for informational and educational purposes only and does not provide professional, legal, or financial advice. Neither the course creator nor the platform hosting this course shall be held liable for any decisions or actions taken based on the content presented.Disclaimer #2: This course uses Generative AI(Artificial Intelligence) to support an enhanced learning experience. About the Instructor: Hi, I'm Deshan and I'm a Digital Transformation Consultant. I have a M. Sc. in Technology Management (Distinction) from the Staffordshire University, UK as well as First Class Honors in B. Sc. (Applied Information Technology) from the Staffordshire University, UK. I also have around 10 years of experience in coding websites and software; creating multimedia, illustrations and graphics as well as computer simulation and 3D modelling! Feel free to ask any question regarding Digital Transformation, Industry 4.0 and Digital Disruption in the forum!

Explore data mining techniques using Python in this comprehensive 56-minute tutorial for beginners. Learn the fundamentals of data mining, including classification, regression, and prediction. Discover how to implement these concepts using Python to extract valuable insights from data, potentially boosting company revenue, expanding market segments, or even contributing to medical breakthroughs. Gain practical skills through hands-on examples and access additional resources for further learning in data science and business analytics.

Discover how researchers at the European Molecular Biology Laboratory (EMBL) leveraged managed Kubernetes to accelerate their analysis of large biomedical omics datasets. Learn about the challenges faced by EMBL's development team in processing massive amounts of spatial metabolomics data, often exceeding 1TB, and how they overcame these obstacles using IBM Cloud Code Engine. Explore the benefits of focusing on research and analytic engine development rather than managing complex Kubernetes infrastructure. Gain insights into speeding up delivery cycles and producing timely results in molecular biology and medicine research without requiring extensive Kubernetes expertise.

Learn Regression Techniques, Data Mining, Forecasting, Text Mining using R What you'll learn: Learn about the basic statistics, including measures of central tendency, dispersion, skewness, kurtosis, graphical representation, probability, probability distribution, etc.Learn about scatter diagram, correlation coefficient, confidence interval, Z distribution & t distribution, which are all required for Linear Regression understandingLearn about the usage of R for building Linear RegressionLearn about the K-Means clustering algorithm & how to use R to accomplish thisLearn about the science behind text mining, word cloud & sentiment analysis & accomplish the same using R Data Science using Ris designed to cover majority of the capabilities of Rfrom Analytics & Data Science perspective, which includes the following: Learn about the basic statistics, including measures of central tendency, dispersion, skewness, kurtosis, graphical representation, probability, probability distribution, etc.Learn about scatter diagram, correlation coefficient, confidence interval, Z distribution & t distribution, which are all required for Linear Regression understandingLearn about the usage of Rfor buildingRegression modelsLearn about the K-Means clustering algorithm & how to use Rto accomplish the sameLearn about the science behind text mining, word cloud,sentiment analysis & accomplish the same using RLearn about Forecasting models including AR, MA, ES, ARMA, ARIMA, etc., and how to accomplish the same using RLearn about Logistic Regression & how to accomplish the same using R

The course is based on the text Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman, and Jeff Ullman, who by coincidence are also the instructors for the course. The book is published by Cambridge Univ. Press, but by arrangement with the publisher, you can download a free copy Here. The material in this on-line course closely matches the content of the Stanford course CS246. The major topics covered include: MapReduce systems and algorithms, Locality-sensitive hashing, Algorithms for data streams, PageRank and Web-link analysis, Frequent itemset analysis, Clustering, Computational advertising, Recommendation systems, Social-network graphs, Dimensionality reduction, and Machine-learning algorithms.