230 Mining courses delivered Online

Uncover Earth's Secrets with Our Geology Course 🌍 Are you ready to embark on an exciting journey deep into the heart of our planet? Look no further than our comprehensive Geology course! 🏔️ Delve into the mysteries of Earth's formation, its dynamic processes, and the incredible forces that shape our world every day. Why Choose Our Geology Course? 🌋 Explore the Wonders of the Earth: Geology isn't just about rocks and minerals-it's a captivating study of the Earth's history, its landscapes, and the fascinating stories written in its layers. 🔍 Discover Hidden Treasures: Uncover the secrets hidden beneath the surface as you learn about the forces of erosion, tectonic plate movements, volcanic activity, and so much more. 📚 Expert Guidance: Our course is crafted by seasoned geologists and educators who are passionate about sharing their knowledge and expertise with you. Get ready for an immersive learning experience! 🌟 Hands-on Learning: From field trips to virtual simulations, our course offers hands-on experiences that bring geology to life. Whether you're studying the formation of mountains or examining fossils, you'll have the opportunity to get up close and personal with Earth's wonders. 💡 Practical Applications: Geology isn't just an academic pursuit-it's a field with real-world applications. Gain insights into how geological knowledge is used in industries such as mining, environmental conservation, and natural resource management. Who is this for? Our Geology course is perfect for: Students: Whether you're studying earth sciences, geography, or simply have a passion for understanding the world around you, our course will deepen your understanding of the Earth's processes. Professionals: Are you working in fields such as environmental science, civil engineering, or resource exploration? Our Geology course provides valuable insights that can enhance your expertise and career prospects. Curious Minds: If you've ever looked at a mountain or a rock formation and wondered about its story, this course is for you! Geology is a fascinating subject that appeals to anyone with a sense of curiosity about the natural world. Career Path A Geology course opens doors to a wide range of exciting career opportunities, including: 🏗️ Environmental Consultant: Help businesses and organizations navigate environmental regulations and assess the impact of human activities on natural landscapes. ️ Geologist: Work in fields such as mineral exploration, oil and gas extraction, or geological surveys, contributing to our understanding of Earth's resources and structures. 🌿 Environmental Scientist: Study the interactions between human activities and the natural environment, working to protect ecosystems and promote sustainability. 🌎 Park Ranger: Combine your love of the outdoors with your knowledge of geology by working in national parks or protected areas, educating visitors and preserving natural landscapes. 📊 Data Analyst: Analyze geological data to identify patterns, trends, and potential risks, contributing to informed decision-making in various industries. FAQ Q: Is this course suitable for beginners? A: Absolutely! Our Geology course is designed to accommodate learners of all levels, from beginners to advanced students. Our instructors provide clear explanations and support to help you grasp the fundamentals of geology. Q: What materials do I need for this course? A: All you need is a curious mind and a passion for exploring the natural world! While specific materials may vary depending on the course format, we'll provide you with everything you need to succeed, whether it's textbooks, online resources, or field trip equipment. Q: Can I take this course online? A: Yes! Our Geology course offers both in-person and online learning options to accommodate your schedule and preferences. Experience the thrill of discovery from the comfort of your own home or join us in the field for hands-on exploration-it's up to you! Q: Will this course help me find a job in the field of geology? A: While completion of our Geology course is not a guarantee of employment, it provides valuable knowledge and skills that can enhance your career prospects in geology-related fields. Networking opportunities, practical experience, and a solid understanding of geological principles can help you stand out to potential employers. Enroll Today and Uncover the Secrets of the Earth! Don't miss out on the opportunity to explore the wonders of geology and gain a deeper appreciation for the world beneath your feet. Enroll in our Geology course today and embark on a journey of discovery that will expand your horizons and ignite your passion for the natural world! 🌟 Course Curriculum Module 1 Introduction to Geology. Introduction to Geology. 00:00 Module 2 Earths Structure and Plate Tectonics. Earth_s Structure and Plate Tectonics. 00:00 Module 3 Surface Processes and Landscape Evolution. Surface Processes and Landscape Evolution. 00:00 Module 4 Earths Interior and Geophysical Processes. Earth_s Interior and Geophysical Processes. 00:00 Module 5 Earth Materials and Minerals. Earth Materials and Minerals. 00:00 Module 6 Geological Time and Earth_s History. Geological Time and Earth_s History. 00:00

In this course, we will process massive streams of real-time data using Spark Streaming and create Spark applications using the Scala programming language (v2.12). We will also get our hands-on with some real live Twitter data, simulated streams of Apache access logs, and even data used to train machine learning models.

Unlock the potential of business intelligence with our specialized Business Intelligence Analyst Course. Learn to analyze data, extract insights, and drive strategic decisions to optimize business performance. Gain practical skills in data visualization, reporting, and predictive analytics using industry-leading tools and techniques. Whether you're a business professional or aspiring analyst, this course equips you with the expertise to excel in leveraging data for business intelligence.

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Getting Started The Level 7 Diploma in Logistics and Supply Chain Crisis Management will require learners to critically assess a broad spectrum of occupational health and safety implementation standards, risk assessment techniques, and models. Additionally, they will be expected to apply data mining methods in practical scenarios. The Qualifi Level 7 Diploma in Logistics and Supply Chain Crisis Management is designed to offer learners the following opportunities: Attain a recognized qualification from an internationally acclaimed awarding organization. Engage with a curriculum enriched with up-to-date content pertinent to the contemporary business landscape. Cultivate fresh skills and knowledge that can be promptly applied, particularly in the domain of supply chain risk and resilience management. Prepare for advanced leadership and be taught by esteemed academic and practitioner experts who possess practical experience across various logistics and supply chain sectors.   Key Benefits Assess and provide critical evaluations of various approaches and implementation standards relevant to logistics and supply chain operations. Appraise the significance of strategic leadership in the realm of supply chain risk management. Examine the consequences of globalization on the extended logistics and supply chain operations of organizations. Demonstrate an understanding of sustainability principles and their application in supply chain leadership. Analyse problem-solving techniques tailored to the specific demands of supply chain crisis management and resilience development. Effectively manage strategic risks and foster resilience within a global supply chain context. Key Highlights Are you a practicing logistics professional seeking a deeper understanding of the industry and aiming to advance into senior positions? Then, the Qualifi Level 7 Diploma in Logistics and Supply Chain Crisis Management is the ideal starting point for your career journey. This course will help you build a career and prepare individuals for future roles in the health and social care sector. Remember, the assessment for this qualification is based on assignments only, so you don't need to worry about taking exams. With the School of Business and Technology London, you can complete the qualification at your own pace, choosing online or blended learning from the comfort of your home. Learning materials, pathway materials, and study guides developed by our Qualifi-approved tutors will be available around the clock in our cutting-edge learning management system. Most importantly, at the School of Business and Technology London, we offer comprehensive tutor support through our dedicated support desk. If you choose the blended learning option, you can also enjoy live sessions with an assigned tutor, which you can book at your convenience.   Career Pathways Upon completion of the Level 7 Diploma in Logistics and Supply Chain Crisis Management, graduates may pursue various career paths in education and training, such as: Logistic Manager, with an average salary of £49,453 per year Supply Chain Analyst, with an average salary of £35,380 per year Inventory Manager, with an average salary of £32,000 per year Warehouse Manager, with an average salary ranging from £50,000 to £60,000 per year   About Awarding Body QUALIFI, recognised by Ofqual awarding organisation has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Leadership, Hospitality & Catering, Health and Social Care, Enterprise and Management, Process Outsourcing and Public Services. They are liable for awarding organisations and thereby ensuring quality assurance in Wales and Northern Ireland. What is included? Outstanding tutor support that gives you supportive guidance all through the course accomplishment through the SBTL Support Desk Portal. Access our cutting-edge learning management platform to access vital learning resources and communicate with the support desk team. Quality learning materials such as structured lecture notes, study guides, and practical applications, which include real-world examples and case studies, will enable you to apply your knowledge. Learning materials are provided in one of the three formats: PDF, PowerPoint, or Interactive Text Content on the learning portal. The tutors will provide Formative assessment feedback to improve the learners' achievements. Assessment materials are accessible through our online learning platform. Supervision for all modules. Multiplatform accessibility through an online learning platform facilitates SBTL in providing learners with course materials directly through smartphones, laptops, tablets or desktops, allowing students to study at their convenience. Live Classes (for Blended Learning Students only) Assessment Assignment based Assessment No exam Entry Requirements The qualification has been intentionally structured to promote accessibility, eliminating artificial obstacles that may hinder entry and advancement. Prospective learners will gain admission through a center interview if they meet at least one of the following criteria: Possession of a Level 6 qualification in a related field. Holding a Bachelor's degree. Accumulating a minimum of 3 years of managerial work experience that substantiates current and pertinent industry expertise. Progression Upon successful completion of the QUALIFI Level 7 Diploma in Logistics and Supply Chain Crisis Management, learners have multiple avenues for progression, including: Advancing to a QUALIFI Level 7 and 8 Diploma. Direct entry into employment within a relevant professional field. Pursuing a suitable dissertation-only program for a Master's Degree in collaboration with one of our university partnerships Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable. Learners are not allowed to make any request to interchange unit(s) once enrolment is complete. UNIT1- Critical Issues - Strategic Framework for Understanding Risk and Resilience Building Reference No : M/618/2775 Credit : 20 || TQT : 200 The primary aim of this unit is to empower learners to recognize, coordinate, and execute the necessary activities and procedures essential for devising logistics and supply chain strategies. UNIT2- Engineering Systems Views of Supply Chain Resilience Reference No : T/618/2776 Credit : 20 || TQT : 200 In this unit, learners will explore the process of constructing systems views in conjunction with relevant theories and practices. UNIT3- Sector-Specific Supply Chain Resilience Management Reference No : A/618/2777 Credit : 20 || TQT : 200 This unit will facilitate learners in comprehending the dynamics of comprehensive supply chains and the managerial decisions necessary to uphold risk mitigation strategies and resilience planning. UNIT4- Ethical and Social Supply Chain Management Reference No : F/618/2778 Credit : 20 || TQT : 200 The primary objective of this unit is to afford learners the chance to assess the fundamental concepts of ethical considerations and social capital within the context of contemporary global supply chains. UNIT5- Critical Issues - Supply Chain Crime, Corruption, and Terrorism Reference No : J/618/2779 Credit : 20 || TQT : 200 This unit is structured to direct learners' focus toward strategic concerns that require attention within the logistics and supply chain industry, with a particular emphasis on concealed elements like crime, corruption, and terrorism. UNIT6- Critical Issues - Management of Supply Chains During Natural Disasters, Climate Change, and Pandemics Reference No : A/618/2780 Credit : 20 || TQT : 200 The objective of this unit is to engage in a critical discussion and reflection on contemporary and emerging challenges associated with managing operations in the aftermath of climate change, natural disasters, and pandemic-type events. Delivery Methods School of Business & Technology London provides various flexible delivery methods to its learners, including online learning and blended learning. Thus, learners can choose the mode of study as per their choice and convenience. The program is self-paced and accomplished through our cutting-edge Learning Management System. Learners can interact with tutors by messaging through the SBTL Support Desk Portal System to discuss the course materials, get guidance and assistance and request assessment feedbacks on assignments. We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue an innovative learning approach where traditional regular classroom-based learning is replaced by web-based learning and incredibly high support level. Learners enrolled at SBTL are allocated a dedicated tutor, whether online or blended learning, who provide learners with comprehensive guidance and support from start to finish. The significant difference between blended learning and online learning methods at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions, which can be booked in advance on their convenience at additional cost. These live sessions are relevant to the learners' program of study and aim to enhance the student's comprehension of research, methodology and other essential study skills. We try to make these live sessions as communicating as possible by providing interactive activities and presentations. Resources and Support School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently. Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receive a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.

Learn Python programming by developing robust GUIs and games

Bring Your Data To Life | Designed by Industry Specialist | Level 7 | QLS Endorsed Diploma | Certificate Included

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

This course covers the Django web framework from the beginning and also covers advanced Django features. Besides Django, the course also covers HTML, CSS, and Bootstrap, which will introduce full-stack development with Django so that you can build complete web apps from scratch. Learn to develop your own web applications with the help of this course.

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm