Overview This comprehensive course on CompTIA Healthcare IT Technician will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This CompTIA Healthcare IT Technician comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this CompTIA Healthcare IT Technician. It is available to all students, of all academic backgrounds. Requirements Our CompTIA Healthcare IT Technician is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 6 sections • 27 lectures • 06:02:00 total length •Core Concepts in Healthcare IT 00:06:00 •EMR EHR Issues: 00:05:00 •Regulations, Standards, and Stakeholders: 00:14:00 •HIPAA Controls and Compliance: 00:08:00 •Healthcare Organizations: 00:14:00 •Medical Terminology, Equipment, and Software: 00:12:00 •Medical Coding and Billing: 00:05:00 •Medical Computer Interfaces: 00:07:00 •Roles and Responsibilities: 00:10:00 •Manage Communication and Ethics Issues: 00:15:00 •Legal Best Practices, Requirements, and Documentation: 00:09:00 •Medical Document Imaging: 00:04:00 •Sanitation Management: 00:03:00 •Computing Essentials: 00:05:00 •Networking: 00:33:00 •Manage Servers and Software: 00:27:00 •Hardware Support: 00:14:00 •Set Up a Workstation: 00:08:00 •Troubleshoot Basic IT Issues: 00:15:00 •Troubleshoot Medical IT Issues: 00:20:00 •Implementation of an EMR EHR System: 00:34:00 •Change Control: 00:08:00 •Manage Physical and Logical Security: 00:36:00 •Implement Security Best Practices and Threat Mitigation Techniques: 00:13:00 •Manage Remote Access: 00:06:00 •Manage Wireless Security: 00:15:00 •Perform Backups and Disaster Recovery: 00:16:00
Duration 3 Days 18 CPD hours This course is intended for This course is designed for the following roles: System administrators Technical solutions architects Systems integrators Channel partners Value-added resellers Customer sales engineers DevOps engineers Sales engineers Systems engineers Technical solutions architects Overview This course will help you: Use SaaS or on-prem version of Cisco Intersight to enable IT organizations to analyze, simplify, and automate their environments in more advanced ways than the prior generations of tools Gain hands-on experience using Cisco Intersight Understand the X-Series, B-Series, and C-Series product line similarities and differences Describe Cisco Intersight and how it can be used to manage UCS and Cisco Hyperflex Understand the process for upgrading firmware with Cisco Intersight Administering server profiles, pools, and policies with Cisco Intersight Describe how to get started with Cisco Intersight programmability Cisco Intersight Overview (DCISO) v1.0 is a 3-day instructor led course that builds your experience with the administration of Cisco Unified Computing System (UCS) X-Series servers, including using Cisco Intersight for UCS management. This course covers architecture, configuration, and operation of Cisco Intersight©, and is designed to serve the needs of engineers seeking to understand the capabilities of Cisco Intersight for managing data centers from a single management platform. Course Outline Describing Cisco UCS Management in Cisco Intersight Describing the Cisco UCS Platform Describing Cisco Intersight Workloads Describing Automation Options Using Cisco Intersight
Feeling Stuck in Your Career? The IT Security: CompTIA network+ with SQL -(30 in 1 Bundle) Bundle is Your Skill-Building Solution. This exceptional collection of 30 premium courses is designed to encourage growth and improve your career opportunities. Suited to meet different interests and goals, the IT Security: CompTIA network+ with SQL bundle provides an engaging learning experience, helping you learn skills across various disciplines. With IT Security: CompTIA network+ with SQL -(30 in 1 Bundle) Bundle, you'll have a personalised journey that aligns with your career goals and interests. This comprehensive package helps you confidently tackle new challenges, whether entering a new field or enhancing your existing knowledge. The IT Security: CompTIA network+ with SQL bundle is your gateway to expanding your career options, increasing job demand, and enhancing your skill set. 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Learn Orchestration and Automation in DevOps with Puppet with lectures, demos, and hands-on coding exercises
***24 Hour Limited Time Flash Sale*** Computer Maintenance Admission Gifts FREE PDF & Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter Do you ever feel frustrated by your computer running slow, crashing unexpectedly or showing error messages? According to a recent study by YouGov, nearly 70% of UK adults have experienced a computer problem they couldn't fix themselves. This comprehensive Computer Maintenance Bundle equips you with the skills to not only troubleshoot these everyday issues but potentially pursue a career in IT support. Are you ready to take control of your technology and maybe even help others with theirs? This extensive bundle offers a one-stop shop for everything computer maintenance related. Whether you're a complete beginner or an experienced IT professional, you'll find a course to suit your needs. 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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
The 'Unix Administration: Unix Operating System' course offers a comprehensive introduction to Unix, focusing on key concepts, file and directory management, essential commands, and the basics of the VI text editor. Participants will gain practical knowledge and skills in Unix administration, enabling them to navigate and manage the Unix operating system effectively. Learning Outcomes: Understand the fundamentals of Unix and its significance in modern computing. Explore directory and file management techniques, including creation, manipulation, and organization. Master essential Unix commands for tasks such as navigation, file operations, and system management. Learn the basics of the VI text editor for efficient file editing and manipulation. Acquire proficiency in using Unix shell commands to enhance system administration. Develop skills in managing user accounts, permissions, and security settings. Gain knowledge of process management and system monitoring in Unix. Understand basic networking concepts and how they apply to Unix systems. Why buy this Unix Administration: Unix Operating System? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Unix Administration: Unix Operating System there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Unix Administration: Unix Operating System does not require you to have any prior qualifications or experience. You can just enrol and start learning. IT professionals seeking to enhance their Unix administration skills. System administrators and network administrators working with Unix-based systems. Software developers and programmers interested in Unix environments. Students and enthusiasts looking to gain hands-on experience with Unix. Individuals pursuing a career in IT infrastructure and system management. Prerequisites This Unix Administration: Unix Operating System was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Unix System Administrator - Median salary of £40,000 - £50,000 per year. Network Administrator - Median salary of £30,000 - £40,000 per year. IT Operations Manager - Median salary of £50,000 - £70,000 per year. Software Developer - Median salary of £35,000 - £45,000 per year. IT Consultant - Median salary of £40,000 - £60,000 per year. Course Curriculum Unix Administration: Unix Operating System Introduction to Unix 01:00:00 Directory and File Management (Part- I) 00:58:00 Directory and File Management (Part- II) 00:59:00 Commands in Unix 00:59:00 Basics of VI Editor 00:59:00 Assignment Assignment - Unix Administration: Unix Operating System 00:00:00
Getting Started The main aim of the OTHM Level 7 Diploma in Data Science is to enhance the knowledge and skills required to extract business-oriented insights from data. This involves comprehending how value and information circulate in a business and utilising this knowledge to recognise potential business prospects.The main aim of the OTHM Level 7 Diploma in Data Science is to enhance the knowledge and skills required to extract business-oriented insights from data. This involves comprehending how value and information circulate in a business and utilising this knowledge to recognise potential business prospects. Key Benefits This qualification will bring you many vital benefits, such as; Learners can gain the essential subject knowledge needed to progress successfully into further study or the world of work. Refreshed content that is closely aligned with employer and higher education needs Develop a comprehensive knowledge of classical data analytics, including statistical inference, predictive modelling, time series analysis and data reduction. Become familiar with and use the tools and techniques used in data visualisation. Assessments that consider cognitive skills along with affective and applied skills Key Highlights Do you wish to be a Data Scientist? Then, The OTHM Level 7 Diploma in Data Science program offered by the School of Business and Technology London is the right solution for you. Remember! The assessment for the qualification is done based on assignments only, and you do not need to worry about writing any exam. 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 and pathway materials and study guides developed by our OTHM-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 will provide comprehensive tutor support through our dedicated support desk. If you choose your course with blended learning, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways The OTHM Level 7 Diploma in Data Science can open many career pathways including, but not limited to: Data scientist- Est. Salary £59,680 Data Analyst- Est. Salary £42,984 Business Analyst-Est. Salary £54,413 About Awarding Body OTHM is an established and recognised Awarding Organisation (Certification Body) launched in 2003. OTHM has already made a mark in the UK and global online education scenario by creating and maintaining a user-friendly and skill based learning environment. OTHM has both local and international recognition which aids OTHM graduates to enhance their employability skills as well as allowing them to join degree and/or Master top-up programmes. OTHM qualifications has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Business Studies, Leadership, Tourism and Hospitality Management, Health and Social Care, Information Technology, Accounting and Finance, Logistics and Supply Chain Management. 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- Data Science Foundations Reference No : Unit 1 - F/650/5562 Credit : 20 || TQT : 200 Hours This unit introduces various data science concepts, including data administration, governance, and big data sources. UNIT2- Probability and Statistics for Data Analysis Reference No : Unit 2 - H/650/5563 Credit : 20 || TQT : 200 Hours The objective of this unit is to offer a comprehensive introduction to the fundamental principles of probability and statistics, starting from the basics. It will cover a wide spectrum of data analysis procedures and methodologies. UNIT3- Advanced Predictive Modeling Reference No : Unit 3 - J/650/5564 Credit : 20 || TQT : 200 Hours You will become acquainted with key predictive modelling methods and their underlying foundational principles in this unit. UNIT4- Data Analysis and Visualisation Reference No : Unit 4 - K/650/5565 Credit : 20 || TQT : 200 Hours This unit serves as a crucial foundation for grasping the core concepts of the data analysis process, encompassing data collection, data cleansing, data analysis, and the effective communication of insights through visualisations and dashboard tools. UNIT5- Data Mining Machine Learning and Artificial Intelligence Reference No : Unit 5 - J/650/5573 Credit : 20 || TQT : 200 Hours The primary aim of this unit is to provide an introduction to the scientific principles underpinning machine intelligence and to explore the philosophical discourse surrounding the endeavour to simulate human intelligence for addressing real-world challenges. UNIT6- Advanced Computing Research Methods Reference No : Unit 6 - L/650/5566 Credit : 20 || TQT : 200 Hours This unit aims to enhance learners' skills in preparing for diverse forms of academic computing research by guiding them through creating and designing a research proposal. 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.
24 Hours Left! Don't Let Winter Sale Slip Away - Enrol Now! With over 100,000 civil engineers in the UK, the demand for data-savvy professionals is high. According to a recent study, 72% of UK civil engineering firms are investing in data analytics to enhance decision-making processes, with data engineering experiencing a 40% year-on-year growth. This surge outpaces other tech sectors, highlighting the critical role of data engineers in big data and advanced analytics. This Data Engineering bundle empowers you to capitalise on this growing trend, equipping you with the proficiency to extract valuable insights from vast datasets, optimise project planning, and enhance overall efficiency. Embark on a transformative journey with our Data Engineering Bundle, thoroughly crafted to bridge the skill gap in one of the UK's fastest-growing job markets. Our bundle offers a comprehensive exploration into the world of data, equipping you with the analytical prowess to harness, process, and visualise data effectively. From mastering SQL programming to delving into the complexities of machine learning with R, this bundle is your gateway to becoming a data engineering maestro. In today's data-driven landscape, possessing a robust set of analytical skills is no longer a luxury but a necessity. With an emphasis on Data engineering, our courses are designed to foster a deep understanding of data analytics, visualisation, and mining, ensuring you can convert raw data into strategic insights that propel business decisions. Seize the opportunity to be at the helm of innovation and become the architect of tomorrow's data landscape with our Data Engineering Bundle. Join us now! Courses are Included in This Data Engineering Bundle: Course 01: Introduction to Data Analysis Course 02: Data Science & Machine Learning with R Course 03: Data Analytics with Tableau Course 04: SQL Programming Masterclass Course 05: Excel Pivot table for Data analytics Course 06: Data analytics with Excel Course 07: Python for Data Analysis Course 08: Basic Google Data Studio Course 09: Business Intelligence and Data Mining Masterclass Course 10: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query Course 11: JavaScript Functions for Data Analyst Course 12: GDPR Data Protection Level 5 Course 13: GDPR Training Course 14: Learn Programming with Python Course 15: Data Center Training Essentials: General Introduction Course 16: Quick Data Science Approach from Scratch Course 17: Statistics & Probability for Data Science & Machine Learning Course 18: Master JavaScript with Data Visualization Course 19: Excel Data Tools and Data Management Course 20: Cloud Computing Essentials for Data Analysis Learning Outcomes of Data Engineering Bundle: Gain proficiency in SQL for complex database management and analytics tasks. Master R for data science and machine learning applications in various industries. Develop advanced Excel skills, including data analytics and pivot table expertise. Acquire hands-on experience with Tableau for effective data visualisation. Learn Python programming essentials for data analysis and engineering solutions. Understand Google Data Studio to create dynamic reports and dashboards. Why Choose Our Data Engineering Course? FREE Data Engineering certificate accredited Get a free student ID card with Data Engineering Training Get instant access to this Data Engineering course. Learn Data Engineering from anywhere in the world The Data Engineering is affordable and simple to understand The Data Engineering is an entirely online, interactive lesson with voiceover audio Lifetime access to the Data Engineering course materials The Data Engineering comes with 24/7 tutor support Start your learning journey straightaway with our Data Engineering Bundle! This Data Engineering bundle will equip you with the skills and knowledge to become a data-savvy civil engineer. You will learn how to collect, analyze, and interpret data to improve infrastructure projects and processes. This Data Engineering bundle includes courses on data analysis, data science, machine learning, SQL programming, Excel pivot tables, Excel data analytics, Python for data analysis, Google Data Studio, business intelligence, data mining, GDPR data protection, JavaScript functions for data analysts, and Python programming. Assessment Process of Data Engineering Once you have completed all the courses in the Data Engineering bundle, you can assess your skills and knowledge with an optional assignment. Our expert trainers will assess your assignment and give you feedback afterwards. CPD 200 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Data Engineering bundle is suitable for everyone. Also, our Data Engineering Bundle is perfect for: Aspiring data engineers Business intelligence analysts Data-driven marketers IT professionals Statistics enthusiasts Career changers Requirements You will not need any prior background or expertise in the Data Engineering Bundle. Career path This Data Engineering bundle will allow you to kickstart or take your career to the next stage in the related sector such as: Data Analyst BI Developer ML Engineer Data Scientist Database Administrator Data Strategist Certificates CPD Accredited Digital Certificate Digital certificate - Included CPD Accredited Hard Copy Certificate Hard copy certificate - Included If you are an international student, then you have to pay an additional 10 GBP for each certificate as an international delivery charge.