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Overview This comprehensive course on Clinical Data Analysis with SAS will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Clinical Data Analysis with SAS comes with accredited certification, 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 Clinical Data Analysis with SAS. It is available to all students, of all academic backgrounds. Requirements Our Clinical Data Analysis with SAS 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 Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 5 sections • 30 lectures • 01:54:00 total length •Course Promo: 00:01:00 •1.1 Components of the Pharma Industry: 00:05:00 •1.2 Phases of Clinical Trials: 00:06:00 •1.3 Data and Reports in Clinical Trials: 00:04:00 •1.4 Types of Data: 00:05:00 •2.1 Clinical Study Protocol: 00:02:00 •2.2 Ethical Consent: 00:01:00 •2.3 Inclusion-Exclusion Criteria: 00:01:00 •2.4 Statistical Analysis Plan: SAP, Mockshell and CRF: 00:04:00 •3.1 General SAS Programming Steps: 00:02:00 •3.2 One Search Report: Demographics Table: 00:04:00 •3.3 Understanding the Demographics Table: 00:03:00 •3.4 Programming the Demographics Table: 00:05:00 •3.5 Importing Raw Demographic Data into the SAS: 00:04:00 •3.6 Deciding what Procedure to Use: 00:02:00 •3.7 Deriving the AGE variable: 00:10:00 •3.8 Obtaining Summary Statistics for AGE: 00:04:00 •3.9 Adding the 3rd Treatment Group using Explicit Output: 00:05:00 •3.10 Deriving the SEX variable: 00:03:00 •3.11 Obtaining Summary Statistics for SEX: 00:03:00 •3.12 Concatenating the COUNT and PERCENT Variables: 00:03:00 •3.13 Deriving the RACE Variable: 00:03:00 •3.14 Obtaining Summary Statistics for RACE: 00:03:00 •3.15 Stacking All the 3 Summary Statistics Together: 00:06:00 •3.16 Fixing the Precision Points: 00:04:00 •3.17 Transposing Data: 00:03:00 •3.18 Fixing the Order of Statistical Parameters: 00:05:00 •3.19 Building the Final Report: 00:02:00 •3.20 Putting the Final Touches to the Report: 00:11:00 •Resources - Clinical Data Analysis with SAS: 00:00:00

The Oracle 11g PL/SQL Part 1 course will focus on giving you the best knowledge of coding and designing PL/SQL and SQL scripts. Initially, you'll learn how to start programming in Oracle PL/SQL. You'll understand the history of PL/SQL, installing Oracle Express Edition, connecting to Database, Relational Database, Oracle SQL in an easy-to-grasp method. This course includes mostly practical examples with explanations which makes it more valuable. Upon successful completion of this course, you can have the pleasure to code in PL/SQL which further help to boost your career. From beginners to expert learner can benefit from this course. So enrol today and see what else is in the Oracle 11g PL/SQL Part 1 course. What Will I Learn? Prepare your environment Work with Oracle database tools Understand and work with language features Work with the DECLARE clause Work with the BEGIN clause Work with the EXCEPTION clause Use explicit cursors Understand and use nested blocks Understand the difference between nested blocks and subprograms Requirements Familiarity with database and programming principles Who is the target audience? Application designers and developers Database administrators Business users and non-technical senior end users Introduction Introduction FREE 00:03:00 Preparing Your Environment Course Setup 00:37:00 Working with Oracle Database Tools Selecting the Appropriate Database Tool 00:31:00 Language Features Understanding PL/SQL 00:18:00 PL/SQL Blocks 00:15:00 Working with SQL Plus 00:11:00 The DECLARE Clause DECLARE Clause Objects 00:16:00 PL/SQL Available Data Types 00:17:00 Declaring Simple Data Types and Assignments 00:12:00 Declaring Complex Data Types and Assignments 00:11:00 Declaring Complex RowTypes and Assignments 00:07:00 Declaring Complex Tables 00:08:00 Declaring Complex Records 00:08:00 Creating and Declaring User-Defined Types 00:09:00 The BEGIN Clause What Can Be Included in the BEGIN Clause 00:07:00 Working with CHAR and VARCHAR2 Variables 00:08:00 Handling String Literals 00:08:00 Working with Numeric Variables 00:07:00 Working with Date Variables 00:06:00 Assigning and Using Boolean Variables 00:08:00 Using Comparison Operators 00:07:00 Using SQL Functions 00:06:00 SQL DML within PL/SQL 00:15:00 Using SELECT 00:07:00 Exceptions and Embedded SQL 00:11:00 Using Sequences 00:14:00 Logic Control and Branching 00:07:00 Using GOTO 00:06:00 Working with LOOPS 00:19:00 Creating and Using the Indefinite Loop 00:07:00 Creating and Using the Conditional Loop 00:08:00 Using Nested Loops 00:12:00 Using the If-Then-Else 00:19:00 Using the CASE Statement 00:18:00 The EXCEPTION Clause What Are the Types of Exceptions 00:06:00 Trapping Exceptions 00:06:00 Identify Exception Details 00:11:00 Creating User-Defined Exceptions 00:11:00 Using SQLCODE and SQLERRM Objects 00:09:00 Understand the Implicit Cursor 00:15:00 Creating User-Defined Events 00:12:00 Explicit Cursors Understanding the Concept and Purpose of Explicit Cursors 00:18:00 Learn about Cursor Attributes 00:10:00 Using the Continue Statement 00:06:00 Working with Updateable Cursors 00:19:00 Creating and Using Cursor Parameters 00:15:00 FOR...LOOP Cursors 00:07:00 Nested Blocks Understanding Nested Blocks 00:11:00 Difference between Global vs Local Objects and Exceptions 00:13:00 Declared Subprograms Subprograms: How They Differ from Nested Blocks 00:18:00 Conclusion Conclusion 00:04:00 Course Certification

Meta Description: Explore the dynamic world of Geospatial Technology in this comprehensive course. From GIS basics to advanced spatial analysis techniques, remote sensing, web-based mapping, and geospatial programming, dive into real-world projects and applications. Discover how to manage spatial data, visualize information, and automate processes, equipping yourself with the skills to tackle diverse challenges across industries. Embark on a journey of innovation and exploration in the realm of Geospatial Technology.

Civil Engineering & Construction Management Training Package Details: Number of Courses: 30 Courses Accreditation: CPD Quality Standards Free Certificates:PDF: 30Hardcopy: 30 (Delivery Charge Applicable) Courses Access: Lifetime Instalment Payment Available --------------***------------- Civil Engineering Course 01: Read Construction & Structural Drawing Like Expert Course 02: Diploma in Construction Management Course 03: Quantity Surveyor Diploma Course 04: Building Surveyor Course 05: Land Surveying Course 06: Bricklaying Course 07: Construction Cost Estimation Diploma Course 08: Construction Estimation using RSMeans Course 09: Construction Cost Estimation Using Xactimate Course 10: Cost Estimation for Multiplex Building Using Xactimate Course 11: Property Law and Legislation Course 12: Construction Industry Scheme (CIS) Course 13: WELL Building Standard Course 14: LEED V4: Building Design and Construction Course 15: LEED V4 - Building Design and Construction Architecture & AutoCAD Course 01: Architectural Studies Course 02: AutoCAD Programming using C# with Windows Forms Course 03: CAD Design Course: Assemblies, Modelling And Civil Drawings Course 04: Autocad Electrical Design Course 05: Intermediate Solidworks Course Course 06: Solidworks Foundation Training Course 07: Interior Design Professional Diploma Course 08: Professional Interior Design & Construction Constraction Course 01: Construction Safety Course 02: Fire Safety | Online Course Course 03: Emergency First Aid and Incident Management at Work Course 04: RIDDOR Training Course 05: LOLER Training Course 06: COSHH Training and Safety - Level 2 Course 07: DSEAR Training Benefits you'll get from choosing Apex Learning for this Civil Engineering & Construction Management training: Pay once and get lifetime access Free e-Learning App for engaging reading materials & helpful assistance Certificates, student ID included in a one-time fee Free up your time - don't waste time and money travelling for classes Accessible, informative Civil Engineering & Construction Management modules designed by expert instructors Learn anytime, from anywhere Study from your computer, tablet or mobile device CPD accredited Civil Engineering & Construction Management courses - improve the chance of gaining professional skills CPD 305 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Civil Engineering & Construction Management bundle including- Students Graduates Job Seekers Job Holders Requirements No requirements to enrol this Civil Engineering & Construction Management course. Career path This Civil Engineering & Construction Management bundle will help you learn the necessary skills to explore opportunities such as- Structural Engineer £36,000 - £38,000 per annum Engineer £27,000 - £45,000 per annum Construction Engineer £3,000 - £45,000 per annum Engineer Surveyor £28,000 - £32,500 per annum Civil Engineer £29,000 - £38,000 per annum

The demand for structural engineers has increased in the UK in recent years. This is because millions of structures are being built worldwide every day. And these numbers will never decrease as we constantly need buildings like offices, houses, bridges, and schools; this list will continue. For those thinking of embarking upon a career in structural engineering, this ultimate career bundle will fill you in on everything you need to know about this buoyant industry and provide the necessary knowledge on how to gain your first big break. In the UK, on average, Structural Engineers earn around £38,000 - £55,000 per annum. So enrol in this course and take your next step towards a successful career! Package Details: Number of Courses: 30 Courses Accreditation: CPD Quality Standards Free Certificates:PDF: 30Hardcopy: 30 (Delivery Charge Applicable) Courses Access: Lifetime Instalment Payment Available Structural Engineering Related Courses Course 01: Read Construction & Structural Drawing Like Expert Course 02: Diploma in Construction Management Course 03: Quantity Surveyor Diploma Course 04: Building Surveyor Course 05: Land Surveying Course 06: Bricklaying Course 07: Construction Cost Estimation Diploma Course 08: Construction Estimation using RSMeans Course 09: Construction Cost Estimation Using Xactimate Course 10: Cost Estimation for Multiplex Building Using Xactimate Course 11: Property Law and Legislation Course 12: Construction Industry Scheme (CIS) Course 13: WELL Building Standard Course 14: LEED V4: Building Design and Construction Course 15: LEED V4 - Building Design and Construction Architecture & AutoCAD Related Courses Course 01: Architectural Studies Course 02: AutoCAD Programming using C# with Windows Forms Course 03: CAD Design Course: Assemblies, Modelling And Civil Drawings Course 04: Autocad Electrical Design Course 05: Intermediate Solidworks Course Course 06: Solidworks Foundation Training Course 07: Interior Design Professional Diploma Course 08: Professional Interior Design & Construction Constraction Safety Related Courses Course 01: Construction Safety Course 02: Fire Safety | Online Course Course 03: Emergency First Aid and Incident Management at Work Course 04: RIDDOR Training Course 05: LOLER Training Course 06: COSHH Training and Safety - Level 2 Course 07: DSEAR Training Benefits you'll get from choosing Apex Learning for this training: Pay once and get lifetime access Free e-Learning App for engaging reading materials & helpful assistance Certificates, student ID included in a one-time fee Free up your time - don't waste time and money travelling for classes Accessible, informative modules designed by expert instructors Learn anytime, from anywhere Study from your computer, tablet or mobile device CPD accredited course - improve the chance of gaining professional skills CPD 305 CPD hours / points Accredited by CPD Quality Standards Career path This bundle will help you learn the necessary skills to explore opportunities such as- Structural Engineer £36,000 - £38,000 per annum Engineer £27,000 - £45,000 per annum Construction Engineer £3,000 - £45,000 per annum Engineer Surveyor £28,000 - £32,500 per annum Civil Engineer £29,000 - £38,000 per annum

Contribute towards your RICS CPD requirements for the year with online webinars from Property Elite. This package contains over 30 hours of online webinars (formal CPD), which you can top up with your own informal CPD via structured reading after you watch each recorded session. Perfect for qualified AssocRICS surveyors and Chartered Surveyors, as well as RICS APC and AssocRICS candidates. Our CPD webinars cover topics relevant to most pathways, including both technical and mandatory competencies and current hot topics.

Get hands-on and learn to build a full-stack app using React.js as the frontend and its web API for the backend

Step beyond the basics and dive deeper into Python with our Intermediate Training Course, designed for those who have already dipped their toes into coding and are ready to advance their skills. This course carefully guides you through more intricate concepts such as object-oriented programming, data manipulation, and working with modules and libraries—all essential tools in the modern Python programmer’s toolkit. Whether you want to enhance your coding fluency or prepare for more specialised projects, this course offers the perfect balance of theory and thoughtful explanation, ensuring clarity without drowning you in jargon. Crafted for learners who appreciate precision and clarity, the course content balances informative detail with a touch of wit to keep you engaged without ever feeling like you’re slogging through a manual. Ideal for self-paced study, it fits neatly around your schedule and learning preferences. By the end, you’ll be confidently handling Python’s intermediate-level challenges and writing code that’s not only functional but a little bit clever too. Ready to level up your programming skills? This course is your next smart step. Learning Outcomes: Gain a deeper understanding of intermediate-level Python concepts. Learn how to work with matrices and manipulate lists and dictionaries. Discover how to use Python to solve complex problems and write efficient and elegant code. Understand how to manipulate data structures and perform advanced data analysis tasks. Learn how to use Python to build real-world projects and applications. The Python Intermediate Training course is designed to provide you with the skills and knowledge you need to become a proficient Python developer. Whether you're a beginner or an experienced programmer looking to enhance your Python skills, this course is perfect for you. Starting with the basics of matrices and lists and moving on to more advanced topics, such as dictionaries and data analysis, this course covers everything you need to know to become a proficient Python developer. You'll learn how to manipulate data structures, perform advanced data analysis tasks, and use Python to build real-world projects and applications. ⊱⊱ Python Intermediate Training Course Curriculum Section 01: Introduction Course Introduction Section 02: Matrix in Python Working on Matrix in Python Working on Matrix in Python Continued Performing Sort Section 03: Working on List in Python Merging to Dictionaries Concatenation of List Example Excepting Values in List and Adding those Using for Loop Excepting Values in List and Adding Those Using While Loop Performing Arithmetic Operation on List Data Structure in Python Data Structure in Python Continued Section 04: Lists & Dictionaries in Python List and Dictionary in Python List and Dictionary in Python Continued Various Sorting Methods in Python Part 1 Various Sorting Methods in Python Part 2 Binary Search Example Reversing a String Dictionary Examples More on List and Dictionary Examples String Examples How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Python beginners who want to take their skills to the next level. Experienced programmers who want to expand their Python skills and knowledge. Data analysts who want to use Python for advanced data analysis tasks. Entrepreneurs who want to develop their own Python-based applications. Students who want to enhance their Python skills and prepare for a career in programming. Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Python Developer: £28,000 - £55,000 Data Analyst: £24,000 - £45,000 Software Engineer: £28,000 - £60,000 Technical Lead: £40,000 - £90,000 Chief Technology Officer: £90,000 - £250,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Getting Started The QUALIFI Level 3 Diploma in Data Science aims to offer learners a comprehensive introduction to data science. This Level 3 Diploma provides a modern and all-encompassing overview of data science, artificial intelligence, and machine learning. It covers the evolution of artificial intelligence and machine learning from their beginnings in the late 1950s to the emergence of the "big data" era in the early 2000s. It extends to the current AI and machine learning applications, including the associated challenges. In addition to covering standard machine learning models like linear and logistic regression, decision trees, and k-means clustering, this diploma introduces learners to two emerging areas of data science: synthetic data and graph data science. Moreover, the diploma familiarizes learners with the landscape of data analysis and the relevant analytical tools. It includes introducing Python programming so learners can effectively analyse, explore, and visualize data and implement fundamental data science models. Key Benefits Acquire the essential mathematical and statistical knowledge necessary for conducting fundamental data analysis. Cultivate analytical and machine learning proficiency using Python. Foster a solid grasp of data and its related processes, encompassing data cleaning, data structuring, and data preparation for analysis and visualisation. Gain insight into the expansive data science landscape and ecosystem, including relational databases, graph databases, programming languages like Python, visualisation tools, and various analytical instruments. Develop expertise in comprehending the machine learning procedures, including the ability to discern which algorithms are suited for distinct problems and to navigate the steps involved in constructing, testing, and validating a model. Attain an understanding of contemporary and emerging facets of data science and their applicability to modern challenges Key Highlights This course module prepares learners for higher-level Data science positions through personal and professional development. We will ensure your access to the first-class education needed to achieve your goals and dreams and to maximize future opportunities. 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 qualified 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 Upon completing the QUALIFI Level 3 Diploma in Data Science, learners can advance their studies or pursue employment opportunities. Data Analyst with an estimated average salary of £39,445 per annum Business Intelligence Analyst with an estimated average salary of £40,000 per annum Data entry specialist with an estimated average salary of £22,425 per annum Database Administrator with an estimated average salary of £44,185 per annum 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 Time-constrained scenario-based assignments No examinations Entry Requirements The qualification has been intentionally designed to ensure accessibility without imposing artificial barriers that limit entry. To enrol in this qualification, applicants must be 18 years of age or older. Admittance to the qualification will be managed through centre-led registration processes, which may involve interviews or other appropriate procedures. Despite the presence of advanced mathematics and statistics in higher-level data science courses, encompassing subjects such as linear algebra and differential calculus, this Level 3 Diploma only requires learners to be comfortable with mathematics at the GCSE level. The diploma's mathematical and statistical concepts are based on standard mathematical operations like addition, multiplication, and division. Before commencing the Level 3 Diploma in Data Science, learners are expected to meet the following minimum requirements: i) GCSE Mathematics with a grade of B or higher (equivalent to the new level 6 or above); and ii) GCSE English with a grade of C or higher (equivalent to the new level 4 or above). Furthermore, prior coding experience is not mandatory, although learners should be willing and comfortable with learning Python. Python has been selected for its user-friendly and easily learnable nature. In exceptional circumstances, applicants with substantial experience but lacking formal qualifications may be considered for admission, contingent upon completing an interview and demonstrating their ability to meet the demands of the capability. Progression Upon successful completion of the QUALIFI Level 3 Diploma in Data Science, learners will have several opportunities: Progress to QUALIFI Level 4 Diploma in Data Science: Graduates can advance their education and skills by enrolling in the QUALIFI Level 4 Diploma in Data Science, which offers a more advanced and comprehensive study of the field. Apply for Entry to a UK University for an Undergraduate Degree: This qualification opens doors to higher education, allowing learners to apply for entry to a UK university to pursue an undergraduate degree in a related field, such as data science, computer science, or a related discipline. Progress to Employment in an Associated Profession: Graduates of this program can enter the workforce and seek employment opportunities in professions related to data science, artificial intelligence, machine learning, data analysis, and other relevant fields. These progression options provide learners with a diverse range of opportunities for further education, career advancement, and professional development in the dynamic and rapidly evolving field of data science Why gain a QUALIFI Qualification? This suite of qualifications provides enormous opportunities to learners seeking career and professional development. The highlighting factor of this qualification is that: The learners attain career path support who wish to pursue their career in their denominated sectors; It helps provide a deep understanding of the health and social care sector and managing the organisations, which will, in turn, help enhance the learner's insight into their chosen sector. The qualification provides a real combination of disciplines and skills development opportunities. The Learners attain in-depth awareness concerning the organisation's functioning, aims and processes. They can also explore ways to respond positively to this challenging and complex health and social care environment. The learners will be introduced to managing the wide range of health and social care functions using theory, practice sessions and models that provide valuable knowledge. As a part of this suite of qualifications, the learners will be able to explore and attain hands-on training and experience in this field. Learners also acquire the ability to face and solve issues then and there by exposure to all the Units. The qualification will also help to Apply scientific and evaluative methods to develop those skills. Find out threats and opportunities. Develop knowledge in managerial, organisational and environmental issues. Develop and empower critical thinking and innovativeness to handle problems and difficulties. Practice judgement, own and take responsibility for decisions and actions. Develop the capacity to perceive and reflect on individual learning and improve their social and other transferable aptitudes and skills 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- The Field of Data Science Reference No : H/650/4951 Credit : 6 || TQT : 60 This unit provides learners with an introduction to the field of data science, tracing its origins from the emergence of artificial intelligence and machine learning in the late 1950s, through the advent of the "big data" era in the early 2000s, to its contemporary applications in AI, machine learning, and deep learning, along with the associated challenges. UNIT2- Python for Data Science Reference No : J/650/4952 Credit : 9 || TQT : 90 This unit offers learners an introductory approach to Python programming tailored for data science. It begins by assuming no prior coding knowledge or familiarity with Python and proceeds to elucidate Python's fundamentals, including its design philosophy, syntax, naming conventions, and coding standards. UNIT3- Creating and Interpreting Visualisations in Data Science Reference No : K/650/4953 Credit : 3 || TQT : 30 This unit initiates learners into the realm of fundamental charts and visualisations, teaching them the art of creating and comprehending these graphical representations. It commences by elucidating the significance of visualisations in data comprehension and discerns the characteristics distinguishing effective visualisations from subpar ones. UNIT4- Data and Descriptive Statistics in Data Science Reference No : L/650/4954 Credit : 6 || TQT : 60 The primary objective of this unit is to acquaint learners with the foundational concepts of descriptive statistics and essential methods crucial for data analysis and data science. UNIT5- Fundamentals of Data Analytics Reference No : M/650/4955 Credit : 3 || TQT : 30 This unit will enable learners to distinguish between the roles of a Data Analyst, Data Scientist, and Data Engineer. Additionally, learners can provide an overview of the data ecosystem, encompassing databases and data warehouses, and gain familiarity with prominent vendors and diverse tools within this data ecosystem. UNIT6- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT7- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT8- Machine Learning Methods and Models in Data Science Reference No : T/650/4957 Credit : 3 || TQT : 30 This unit explores the practical applications of various methods in addressing real-world problems. It provides a summary of the key features of these different methods and highlights the challenges associated with each of them. UNIT9- The Machine Learning Process Reference No : Y/650/4958 Credit : 3 || TQT : 30 This unit provides an introduction to the numerous steps and procedures integral to the construction and assessment of machine learning models. UNIT10- Linear Regression in Data Science Reference No : A/650/4959 Credit : 3 || TQT : 30 This unit offers a foundational understanding of simple linear regression models, a crucial concept for predicting the value of one continuous variable based on another. Learners will gain the capability to estimate the best-fit line by computing regression parameters and comprehend the accuracy associated with this line of best-fit. UNIT11- Logistic Regression in Data Science Reference No : H/650/4960 Credit : 3 || TQT : 30 This unit introduces logistic regression, emphasizing its role as a classification algorithm. It delves into the fundamentals of binary logistic regression, covering essential concepts such as the logistic function, Odds ratio, and the Logit function. UNIT12- Decision Trees in Data Science Reference No : J/650/4961 Credit : 3 || TQT : 30 This unit offers an introductory exploration of decision trees' fundamental theory and practical application. It elucidates the process of constructing basic classification trees employing the standard ID3 decision-tree construction algorithm, including the node-splitting criteria based on information theory principles such as Entropy and Information Gain. Additionally, learners will gain hands-on experience in building and assessing decision tree models using Python. UNIT13- K-means clustering in Data Science Reference No : K/650/4962 Credit : 3 || TQT : 30 This unit initiates learners into unsupervised machine learning, focusing on the k-means clustering algorithm. It aims to give learners an intuitive understanding of the k-means clustering method and equip them with the skills to determine the optimal number of clusters. UNIT14- Synthetic Data for Privacy and Security in Data Science Reference No : L/650/4963 Credit : 6 || TQT : 60 This unit is designed to introduce learners to the emerging field of data science, specifically focusing on synthetic data and its applications in enhancing data privacy and security. UNIT15- Graphs and Graph Data Science Reference No : M/650/4964 Credit : 6 || TQT : 60 This unit offers a beginner-friendly introduction to graph theory, a foundational concept that underlies modern graph databases and graph analytics. 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.