Project Team Collaboration with SharePoint Are you a project manager with a team scattered around the globe? Are you using SharePoint just as a document repository? We will show you how to easily collaborate with your team by easily setting up a SharePoint site. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.
Dive into the heart of Big Data Infrastructure, exploring storage systems, distributed file frameworks, and processing paradigms. This course provides a comprehensive understanding of key components like HDFS, Apache Spark, and Cassandra, offering insights into their architecture, use cases, and real-world applications. This course is a deep dive into the complex landscape of Big Data Infrastructure. From unravelling the architecture of Apache Spark to dissecting the benefits of distributed file systems, participants gain expertise in assessing, comparing, and implementing various Big Data storage and processing systems. Scalability, fault-tolerance, and industry-specific case studies add practical depth to theoretical knowledge. After the successful completion of this course, you will be able to: Understand the Components of Big Data Infrastructure, Including Storage Systems, Distributed File Systems, and Processing Frameworks. Identify the Characteristics and Benefits of Distributed File Systems Such as Hadoop Distributed File System (H.D.F.S). Describe the Architecture and Capabilities of Apache Spark and its Role in Big Data Processing. Recognise the Use Cases and Benefits of Apache Cassandra as a Distributed N..O.S.Q.L Database. Compare and Contrast Different Big Data Storage and Processing Systems Such as Hadoop, Spark, and Cassandra. Understand the Scalability and Fault-tolerance Mechanisms Used in Big Data Infrastructure, Such as Sharding and Replication. Appreciate the Challenges Associated with Deploying and Managing Big Data Infrastructure, Such as Hardware and Software Configuration and Security Considerations. Explore the intricacies of Big Data Infrastructure, from understanding storage systems to unraveling the nuances of distributed file frameworks and processing engines. Gain a comprehensive view of scalability, fault-tolerance mechanisms, and industry-specific challenges through engaging case studies. Equip yourself to navigate the dynamic landscape of Big Data with confidence and expertise. VIDEO - Course Structure and Assessment Guidelines Watch this video to gain further insight. Navigating the MSBM Study Portal Watch this video to gain further insight. Interacting with Lectures/Learning Components Watch this video to gain further insight. Big Data Infrastructure Self-paced pre-recorded learning content on this topic. Big Data Infrastructure Put your knowledge to the test with this quiz. Read each question carefully and choose the response that you feel is correct. All MSBM courses are accredited by the relevant partners and awarding bodies. Please refer to MSBM accreditation in about us for more details. There are no strict entry requirements for this course. Work experience will be an added advantage to understanding the content of the course. The certificate is designed to enhance the learner's knowledge in the field. This certificate is for everyone who is eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience. Big Data Infrastructure Engineer Hadoop Administrator Spark Developer Cassandra Database Administrator Big Data Solutions Architect Data Infrastructure Manager NoSQL Database Analyst Big Data Consultant Average Completion Time 2 Weeks Accreditation 3 CPD Hours Level Advanced Start Time Anytime 100% Online Study online with ease. Unlimited Access 24/7 unlimited access with pre-recorded lectures. Low Fees Our fees are low and easy to pay online.
This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.
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Learn visual merchandising best practices with our comprehensive online course. Master retail display design, window dressing, store layouts, promotional techniques, and more. Develop creative skills to increase sales and customer engagement. Gain industry-recognized expertise to start or advance your retail merchandising career.
A course by Sekhar Metla IT Industry Expert RequirementsNo programming experience needed. You will learn everything you need to knowNo software is required in advance of the course (all software used in the course is free)No pre-knowledge is required - you will learn from basic Audience Beginner JavaScript, Python and MSSQL developers curious about data science development Anyone who wants to generate new income streams Anyone who wants to build websites Anyone who wants to become financially independent Anyone who wants to start their own business or become freelance Anyone who wants to become a Full stack web developer Audience Beginner JavaScript, Python and MSSQL developers curious about data science development Anyone who wants to generate new income streams Anyone who wants to build websites Anyone who wants to become financially independent Anyone who wants to start their own business or become freelance Anyone who wants to become a Full stack web developer
Course Overview Clear out all your confusion about cloud computing and learn it from the primary level with the Basic Cloud Computing with Cloud Models course. This course is designed to introduce you to cloud computing fundamentals and to give you the opportunity to add a valuable certificate to your resume. This Basic Cloud Computing with Cloud Models course will provide you with a detailed definition of cloud computing. It will introduce you to the five key characteristics of cloud computing. Here, you will learn what SAAS, PAAS and IAAS are. The course will teach you the process of creating a free Azure account. You will become skilled in managing the Azure account with CL and PowerShell. In the easy to follow module, you will receive valuable information on Amazon Web Services. You will understand the techniques of getting free access to AWS and creating free AWS accounts. This Basic Cloud Computing with Cloud Models course will equip you with the essentials of cloud computing. Enroll in the course and prepare yourself to pursue a career in the relevant industry. Learning Outcomes Learn the definition and importance of cloud computing Familiarize with the five vital characters of cloud computing Understand the process of Azure free account Build the skills to manage Azure with CL and PowerShell Enrich your knowledge of Amazon Web Services Who is this course for? Anyone interested to learn about cloud computing Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path The Basic Cloud Computing with cloud models course is a useful qualification to possess and would be beneficial for any related profession or industry such as: Cloud Support Engineer Cloud Computing Engineer IT Support and Cloud Engineer Cloud Computing Analyst Cloud Computing Administrator Introduction Introduction 00:01:00 The Need for Cloud Computing 00:13:00 The Definition of Cloud Computing 00:05:00 Evolution of Cloud and Cloud Models 00:05:00 What is SAAS , PAAS and IAAS 00:05:00 Who is responsible for Data in cloud 00:10:00 The Five Key Characteristics of Cloud Computing 00:08:00 Benefits of Cloud Computing 00:09:00 CapEx vs OpEx 00:03:00 Cloud DataCenters : Where are they? 00:02:00 What is Gartner Say About Cloud Providers 00:02:00 Please Read This 00:01:00 Let's Talk Azure How to create Azure Free Account 00:02:00 How to Login to Azure Portal 00:10:00 Managing Azure with CLI 00:04:00 Let's Learn AWS Foot Prints of Amazon Web Services 00:14:00 AWS Console Tour 00:10:00 Free access to AWS 00:03:00 Creating a Free AWS Account 00:03:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00
Duration 1 Days 6 CPD hours This course is intended for Individuals with basic computer skills, familiar with concepts related to database structure and terminology, and who want to use SQL to query databases. Overview Upon successful completion of this course, students will be able to: - connect to the SQL Server database and execute a simple query. - include a search condition in a simple query. - use various functions to perform calculations on data. - organize data obtained from a query before it is displayed on-screen. - retrieve data from tables. - format an output, save a result, and generate a report. In this course, students will compose SQL queries to retrieve desired information from a database. 1 - Executing a Simple Query Connect to the SQL Database Query a Database Save a Query Modify a Query Execute a Saved Query 2 - Performing a Conditional Search Search Using a Simple Condition Compare Column Values Search Using Multiple Conditions Search for a Range of Values and Null Values Retrieve Data Based on Patterns 3 - Working with Functions Perform Date Calculations Calculate Data Using Aggregate Functions Manipulate String Values 4 - Organizing Data Sort Data Rank Data Group Data Filter Grouped Data Summarize Grouped Data Use PIVOT and UNPIVOT Operators 5 - Retrieving Data from Tables Combine Results of Two Queries Compare the Results of Two Queries Retrieve Data by Joining Tables Check for Unmatched Records Retrieve Information from a Single Table Using Joins 6 - Presenting Query Results Save the Query Result Generate an XML Report
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ð Unlock the Power of Data with Our Machine Learning Course! ð¤ Are you ready to dive into the revolutionary world of Machine Learning? Welcome to our comprehensive course designed to equip you with the skills and knowledge needed to harness the potential of data-driven decision-making. ð Machine Learning has rapidly emerged as one of the most transformative technologies of the 21st century. From powering intelligent virtual assistants to revolutionizing healthcare diagnostics, its applications are boundless. With our expertly crafted course, you'll embark on a journey that will demystify the complexities of Machine Learning and empower you to leverage its capabilities for diverse purposes. ð¡ Why Machine Learning? In today's data-driven world, organizations across industries are seeking professionals who can extract actionable insights from vast amounts of data. Machine Learning offers the tools and techniques necessary to analyze complex datasets, identify patterns, and make predictions with unprecedented accuracy. By mastering Machine Learning, you'll gain a competitive edge in the job market and position yourself as a valuable asset to any organization. ð What You'll Learn: Our Machine Learning course covers a wide array of topics, including: Fundamentals of Machine Learning algorithms Supervised, unsupervised, and reinforcement learning techniques Data preprocessing and feature engineering Model evaluation and validation Deep learning and neural networks Practical applications and case studies With hands-on projects and real-world examples, you'll not only understand the theory behind Machine Learning but also gain practical experience in implementing algorithms and solving complex problems. Whether you're a beginner or an experienced data professional, our course is tailored to accommodate learners of all levels. ð Who is this for? Our Machine Learning course is ideal for: Aspiring data scientists and analysts Software engineers looking to transition into Machine Learning roles Business professionals seeking to leverage data for strategic decision-making Students and academics interested in exploring the forefront of technology No matter your background or experience level, our course provides a solid foundation in Machine Learning principles and techniques, setting you on the path to success in this rapidly evolving field. ð Career Path: By mastering Machine Learning, you'll open doors to a myriad of exciting career opportunities, including: Data Scientist Machine Learning Engineer AI Researcher Business Intelligence Analyst Data Engineer With the demand for Machine Learning professionals on the rise, employers are actively seeking individuals with the skills and expertise to drive innovation and deliver impactful solutions. Whether you're looking to advance your current career or embark on a new professional journey, our course will equip you with the tools and knowledge needed to thrive in today's competitive job market. ð¼ FAQ: Q: Is prior programming experience required to enroll in the course? A: While prior programming experience can be beneficial, our course is designed to accommodate learners of all backgrounds. We provide comprehensive tutorials and resources to help you grasp the fundamentals of programming and get started with Machine Learning. Q: How long does it take to complete the course? A: The duration of the course varies depending on your pace and level of commitment. On average, most learners complete the course within 3 to 6 months. However, you have the flexibility to study at your own pace and revisit materials as needed. Q: Are there any prerequisites for enrolling in the course? A: While there are no strict prerequisites, familiarity with basic mathematics, statistics, and programming concepts can be advantageous. We provide supplementary materials and support to help you build the necessary foundation for success in the course. Q: Will I receive a certificate upon completion of the course? A: Yes, upon successfully completing the course requirements, you'll receive a certificate of completion that validates your proficiency in Machine Learning concepts and techniques. This certificate can enhance your credentials and demonstrate your expertise to potential employers. Q: How does the course structure accommodate working professionals? A: Our course offers flexible scheduling options, allowing you to balance your studies with your professional and personal commitments. With on-demand access to course materials and resources, you can learn at your own convenience and progress at a pace that suits your lifestyle. Don't miss out on the opportunity to unlock your full potential with our Machine Learning course! Enroll today and embark on a transformative journey that will shape the future of your career. ð⨠Course Curriculum Module 1_ Introduction to Machine Learning Introduction to Machine Learning 00:00 Module 2_ Linear Regression Linear Regression 00:00 Module 3_ Logistic Regression Logistic Regression 00:00 Module 4_ Decision Trees and Random Forests Decision Trees and Random Forests 00:00 Module 5_ Support Vector Machines (SVMs) Support Vector Machines (SVMs) 00:00 Module 6_ k-Nearest Neighbors (k-NN) k-Nearest Neighbors (k-NN) 00:00 Module 7_ Naive Bayes Naive Bayes 00:00 Module 8_ Clustering Clustering 00:00 Module 9_ Dimensionality Reduction Dimensionality Reduction 00:00 Module 10_ Neural Networks Neural Networks 00:00