979 Data Science courses delivered Online

A code-oriented interactive course that will help you build a solid foundation that is essential to excel in all areas of computer science, specifically data science and machine learning. We will apply all concepts through code and focus on the concepts that are more useful for data science, machine learning, and other areas of computer science.

Master Data Science skills using Python and real time project and go from Beginner to Super Advance level

Getting Started The Level 7 Diploma in Data Science empowers learners to formulate research hypotheses, effectively organize, analyze, and visualize data, unveiling innovative solutions that can challenge conventional business assumptions. It aims to support organizations and their managers in critical decision-making by applying various data science techniques and models. The Qualifi Level 7 Diploma in Data Science offers learners the opportunity to: Obtain a globally recognized qualification from a prestigious awarding organization. Access an up-to-date curriculum aligned with the latest developments in the contemporary business landscape. Acquire new skills and knowledge directly applicable to data science and analytics. Benefit from assessments that are evaluated and moderated by respected academic and industry professionals with hands-on experience in data science and analytics. Progress along a pathway toward pursuing a Master's degree or higher qualifications. Key Benefits Attain comprehensive mathematical and statistical expertise for advanced data analysis. Master programming in R, Python, and SQL for proficient data analysis. Develop strong data management skills, including data evaluation, structuring, and cleaning. Learn effective data visualization techniques and tools. Gain a deep understanding of classical data analytics, covering statistical inference, predictive modelling, time series analysis, and data reduction. Apply common machine learning techniques to solve business and other real-world problems. Grasp essential concepts from contemporary business themes. Apply data science and analytics effectively within business and organizational contexts. Key Highlights 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 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 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 Progress along a pathway to gain a Master's degree or beyond. 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 Possess a minimum of a Level 6 qualification in a related sector. Hold a Bachelor's degree. Demonstrate at least three years of relevant work experience showcasing current and pertinent industry knowledge. Individuals with substantial practical experience but lacking formal qualifications may also be considered in exceptional cases. Their eligibility will be determined through an interview process, where they must demonstrate their capacity to meet the program's demands Progression Upon completing the QUALIFI Level 7 Diploma in Data Science, learners have several promising progression pathways: QUALIFI Level 7 and/or 8 Diploma: Graduates can advance their education and expertise by enrolling in a QUALIFI Level 7 and/or Level 8 Diploma, which offers higher-level qualifications in their chosen field. Direct Employment in an Associated Profession: Learners can enter the workforce directly, securing employment in professions related to data science, analytics, and other relevant areas, applying their newly acquired skills and knowledge. Pursue a Master's Degree Dissertation: Graduates also have the option to undertake an appropriate dissertation-only program for a Master's Degree at one of QUALIFI's university partnerships. This pathway allows them to specialize further and advance their academic qualifications. 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. To know about the Qualification Structure, please get in touch with us at: admission@sbusinesslondon.ac.uk 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.

Transform Your Career with Our IT: Data Analysis, Data Science & Data Protection Program - an all-in-one Program Designed for Mastery! Do you know the demand for IT professionals with expertise in data science is skyrocketing? This Ultimate IT: Data Analysis, Data Science & Data Protection Program is your gateway to a thriving career in this dynamic industry. This program is meticulously designed to equip you with the knowledge and skills demanded by hiring managers across various sectors. By enrolling in this IT: Data Analysis, Data Science & Data Protection program, you'll embark on a journey that opens doors to exciting opportunities and empowers you to shape your future in the IT industry. Our IT: Data Analysis, Data Science & Data Protection program will give you a comprehensive understanding of data analysis, from data collection and preparation to data visualisation and communication. You will be equipped with the necessary skills and guidance to uncover insights from data, solve real-world problems, and make informed decisions. Also, you will discover the ethical and legal implications of data handling, how to protect sensitive information & develop a career in this sector. Moreover, we're your dedicated partners on this exciting journey. Our goal isn't just to teach you; it's to support you 24/7 so you can get closer to your dream job. We're so confident with our program that we offer a 100% money-back guarantee, ensuring your complete satisfaction. Learning Outcomes By completing this IT: Data Analysis, Data Science & Data Protection program, you will gain expertise in the following: Data analysis techniques and methodologies. Python programming for data analysis. Business intelligence and data mining. Advanced Excel techniques, including VBA and Power Query. SQL programming and big data technologies. Data Science & Data Protection, Machine Learning with Python and R. Data visualisation with tools like Tableau and Power BI. Statistics and probability for data science. Effective career development and job-seeking skills. Design an engaging resume and excel in the job search. Succeed in interviews, including video interviews. Build a strong LinkedIn profile to connect with professionals and enhance your online visibility in IT: Data Analysis- Data Science & Data Protection field. Courses Included in the Program You get 25 in-demand courses once you enrol in our IT: Data Analysis, Data Science & Data Protection program. => Course 01: Introduction to Data Analysis => Course 02: Data Analytics => Course 03: Python for Data Analysis => Course 04: Basic Google Data Studio => Course 05: Business Intelligence and Data Mining Masterclass => Course 06: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query => Course 07: SQL Programming Masterclass => Course 08: SQL NoSQL Big Data and Hadoop => Course 09: Data Science & Machine Learning with Python => Course 10: Machine Learning with Python => Course 11: Data Science & Machine Learning with R => Course 12: Data Analytics with Tableau => Course 13: Develop Big Data Pipelines with R & Sparklyr & Tableau => Course 14: Complete Introduction to Business Data Analysis Level 3 => Course 15: Data Analysis in Microsoft Excel Complete Training => Course 16: Excel Data Analysis for Beginner => Course 17: GDPR Data Protection Level 5 => Course 18: Master JavaScript with Data Visualization => Course 19: Data Visualization and Reporting with Power BI => Course 20: Statistics & Probability for Data Science & Machine Learning => Course 21: Career Development Plan Fundamentals => Course 22: CV Writing and Job Searching => Course 23: Interview Skills: Ace the Interview => Course 24: Video Job Interview for Job Seekers => Course 25: How to Create a Professional LinkedIn Profile Enrol in our highly regarded IT: Data Analysis, Data Science & Data Protection program, featuring a job-relevant curriculum that ensures your skills align with employer expectations across various sectors. Don't miss this opportunity - your success story starts now! Our IT: Data Analysis, Data Science & Data Protection Program is a comprehensive and industry-relevant journey through data analysis, data science, and IT analytics. With a focus on providing theoretical knowledge and academic depth, this program is your gateway to a promising career in IT: Data Analysis, Data Science & Data Protection sector. Why Choose Us? We take great pride in offering you a great learning experience that stands out. When you consider enrolling in our IT: Data Analysis, Data Science & Data Protection program, you're making a decision that will positively impact your career and knowledge in various aspects related to IT: Data Analysis, Data Science & Data Protection. Here's why choosing us is a smart choice: Updated Materials: We're committed to providing the most up-to-date learning materials. Our dedicated team continuously reviews and updates our content, ensuring you're always learning from the latest sources. When you choose us, you select the most current and relevant information, giving you the edge in your IT career. Flexible Timing: We understand that life can get busy, and you may have existing commitments that can make pursuing further education challenging. That's why we offer flexibility in your study schedule. With our courses, you can learn at your own pace, on your terms. You're in control and can adjust your learning to fit your life. No Hidden Cost: When choosing our program, you won't incur additional expenses. The certification and course materials are all-inclusive within the program's price. You can focus on your studies without worrying about hidden fees. Money-Back Guarantee: Your satisfaction is our top priority. We're so confident in the quality of our courses that we back them up with a 14-day money-back guarantee. We'll refund your investment if you're unsatisfied with your learning experience. Lifetime Access: When you choose to learn with us, you gain access to a course and a lifetime of knowledge. We offer lifetime access to our course materials, allowing you to revisit and refresh your knowledge whenever you need. 24/7 Support: Learning doesn't just happen during traditional working hours; neither should support. Our commitment to your success extends beyond the classroom. We provide 24/7 support, so you can contact us with your questions and concerns anytime. CPD 250 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This IT: Data Analysis, Data Science & Data Protection program is suitable for: Aspiring IT: Data Analysis, Data Science & Data Protection professionals. Students and recent graduates looking to enter the field. Career changers interested in data analytics. Security professionals seeking to upskill in data security. Anyone interested in learning about IT: Data Analysis, Data Science & Data Protection. Requirements No prior experience is required in our IT: Data Analysis, Data Science & Data Protection program. Career path Upon completing the program, you'll get edges in various IT: Data Analysis, data science & data protection-related jobs including: Data Analyst: £25,000 - £45,000 Business Intelligence Analyst: £30,000 - £50,000 Data Scientist: £35,000 - £60,000 Machine Learning Engineer: £40,000 - £70,000 SQL Developer: £30,000 - £55,000 Tableau Developer: £35,000 - £60,000 Power BI Developer: £35,000 - £60,000 Certificates CPD Accredited (e-Certificate) Digital certificate - Included CPD Accredited (Hard Copy Certificate) Hard copy certificate - Included e-Transcript Digital certificate - Included Hard Copy Transcript Hard copy certificate - Included Student ID Card Digital certificate - Included

In this course, you will learn Python fundamentals, and the concepts of the amazing pandas data science library needed to pre-process and prepare the data for machine learning algorithms.

Do you want to master the essential mathematical skills for data science and machine learning? Do you want to learn how to apply statistics and probability to real-world problems and scenarios? If yes, then this course is for you! In this course, you will learn the advanced concepts and techniques of statistics and probability that are widely used in data science and machine learning. You will learn how to describe and analyse data using descriptive statistics, distributions, and probability theory. You will also learn how to perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data. You will gain hands-on experience with practical exercises and projects using Python and R. Learning Outcomes By the end of this course, you will be able to: Apply descriptive statistics, distributions, and probability theory to summarise and visualise data Perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data Use Python and R to implement statistical and machine learning methods Interpret and communicate the results of your analysis using appropriate metrics and visualisations Solve real-world problems and scenarios using statistics and probability Why choose this Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 course for? This course is for anyone who wants to learn the advanced concepts and techniques of statistics and probability for data science and machine learning. This course is suitable for: Data scientists, machine learning engineers, and analysts who want to enhance their skills and knowledge Students and researchers who want to learn the mathematical foundations of data science and machine learning Professionals and managers who want to understand and apply data-driven decision making Hobbyists and enthusiasts who want to explore and learn from data Anyone who loves statistics and probability and wants to challenge themselves Career path Data Scientist (£35,000 - £55,000) Machine Learning Engineer (£40,000 - £60,000) Statistician (£35,000 - £55,000) Data Analyst (£40,000 - £60,000) Business Intelligence Analyst (£45,000 - £65,000) Senior Data Analyst (£50,000 - £70,000) Prerequisites This Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 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. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Section 01: Let's get started Welcome! 00:02:00 What will you learn in this course? 00:06:00 How can you get the most out of it? 00:06:00 Section 02: Descriptive statistics Intro 00:03:00 Mean 00:06:00 Median 00:05:00 Mode 00:04:00 Mean or Median? 00:08:00 Skewness 00:08:00 Practice: Skewness 00:01:00 Solution: Skewness 00:03:00 Range & IQR 00:10:00 Sample vs. Population 00:05:00 Variance & Standard deviation 00:11:00 Impact of Scaling & Shifting 00:19:00 Statistical moments 00:06:00 Section 03: Distributions What is a distribution? 00:10:00 Normal distribution 00:09:00 Z-Scores 00:13:00 Practice: Normal distribution 00:04:00 Solution: Normal distribution 00:07:00 Section 04: Probability theory Intro 00:01:00 Probability Basics 00:10:00 Calculating simple Probabilities 00:05:00 Practice: Simple Probabilities 00:01:00 Quick solution: Simple Probabilities 00:01:00 Detailed solution: Simple Probabilities 00:06:00 Rule of addition 00:13:00 Practice: Rule of addition 00:02:00 Quick solution: Rule of addition 00:01:00 Detailed solution: Rule of addition 00:07:00 Rule of multiplication 00:11:00 Practice: Rule of multiplication 00:01:00 Solution: Rule of multiplication 00:03:00 Bayes Theorem 00:10:00 Bayes Theorem - Practical example 00:07:00 Expected value 00:11:00 Practice: Expected value 00:01:00 Solution: Expected value 00:03:00 Law of Large Numbers 00:08:00 Central Limit Theorem - Theory 00:10:00 Central Limit Theorem - Intuition 00:08:00 Central Limit Theorem - Challenge 00:11:00 Central Limit Theorem - Exercise 00:02:00 Central Limit Theorem - Solution 00:14:00 Binomial distribution 00:16:00 Poisson distribution 00:17:00 Real life problems 00:15:00 Section 05: Hypothesis testing Intro 00:01:00 What is a hypothesis? 00:19:00 Significance level and p-value 00:06:00 Type I and Type II errors 00:05:00 Confidence intervals and margin of error 00:15:00 Excursion: Calculating sample size & power 00:11:00 Performing the hypothesis test 00:20:00 Practice: Hypothesis test 00:01:00 Solution: Hypothesis test 00:06:00 T-test and t-distribution 00:13:00 Proportion testing 00:10:00 Important p-z pairs 00:08:00 Section 06: Regressions Intro 00:02:00 Linear Regression 00:11:00 Correlation coefficient 00:10:00 Practice: Correlation 00:02:00 Solution: Correlation 00:08:00 Practice: Linear Regression 00:01:00 Solution: Linear Regression 00:07:00 Residual, MSE & MAE 00:08:00 Practice: MSE & MAE 00:01:00 Solution: MSE & MAE 00:03:00 Coefficient of determination 00:12:00 Root Mean Square Error 00:06:00 Practice: RMSE 00:01:00 Solution: RMSE 00:02:00 Section 07: Advanced regression & machine learning algorithms Multiple Linear Regression 00:16:00 Overfitting 00:05:00 Polynomial Regression 00:13:00 Logistic Regression 00:09:00 Decision Trees 00:21:00 Regression Trees 00:14:00 Random Forests 00:13:00 Dealing with missing data 00:10:00 Section 08: ANOVA (Analysis of Variance) ANOVA - Basics & Assumptions 00:06:00 One-way ANOVA 00:12:00 F-Distribution 00:10:00 Two-way ANOVA - Sum of Squares 00:16:00 Two-way ANOVA - F-ratio & conclusions 00:11:00 Section 09: Wrap up Wrap up 00:01:00 Assignment Assignment - Statistics & Probability for Data Science & Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 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.

Get involved in a learning adventure, mastering R from foundational basics to advanced techniques. This course is a gateway to the realm of data science. Explore statistical machine learning models and intricacies of deep learning and create interactive Shiny apps. Unleash the power of R and elevate your proficiency in data-driven decision-making.

Start your career as a Data Scientist and earn upto £90,000/ Year Are you ready to unlock the power of Python and dive into the exciting world of data science? Look no further because we have the ultimate solution for you: Introducing our Data Science with Python Course with Career Support and Job Ready Program! Our mission is simple - to be your trusted partner every step of the way, from training to employment. In addition to teaching you the technical skills you need, we will also provide you with career mentoring and support. We will help you build your resume, prepare for interviews, and land your dream job. We also have partnerships with many companies that are hiring Data Scientists, so we can help you get your foot in the door. If you are not happy with our service, we also offer a 100% money-back guarantee. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist! If you have any questions, you can contact us. We will be happy to provide you with all the information you need. Why Choose Us? So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python: Personalised Guidance: We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Data Scientist experience, we will guide you towards honing your skills and developing a strong foundation in Data Science. Tailored CV Building: Crafting an impressive CV is crucial in today's competitive job market. Our team of experts will work closely with you to create a professional CV that showcases your skills and highlights your potential as a Data Scientist. We'll ensure that your CV stands out among the rest, increasing your chances of landing that dream job. 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Here are the courses we will provide once you enrol in the program: Course 01: Ultimate Python Training for Beginners Course 02: Python Intermediate Training Course 03: Python Advanced Training Course 04: SQL for Data Science, Data Analytics and Data Visualization Course 05: Basic Data Analysis Course 06: Develop Big Data Pipelines with R & Sparklyr & Tableau Course 07: Develop Big Data Pipelines with R, Sparklyr & Power BI Course 08: Customer Analytics Training Course 09: Google Analytics for Everyone Course 10: Google Data Studio: Data Analytics Course 11: Big Data Analytics with PySpark Tableau Desktop and MongoDB Course 12: Big Data Analytics with PySpark Power BI and MongoDB Course 13: Excel Data Analysis Course 14: Introduction to Data Analytics with Tableau Course 15: Machine Learning with Python Course Course 16: Python Programming Bible | Networking, GUI, Email, XML, CGI How Can We Offer Job Guarantees? HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector. The Data Scientist with Python Program is completed in 9 easy steps: Step 1: Enrol in the Programme Begin your exciting journey with us by enrolling in the Data Scientist Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied. After you enrol in the Program, you will get lifetime access to 16 premium courses related to Data Scientist. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing! Step 2: Initial One-On-One Counselling Session Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path. Step 3 - Certification upon Course Completion After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject. Step 4: CV Revamping Our team of professionals will build you a compelling CV and LinkedIn profile. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Data Scientist industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently. Step 5: Building Network and Submitting CV We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile. Step 6: Interview Preparation With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills. Step 7: Securing Job Interviews Leveraging our partnerships with leading companies, we'll secure job interviews for you. We'll ensure you get the opportunity to showcase your skills to potential employers and get the dream job you want. Step 8: Post-Interview Support Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job. Step 9: Celebrate Your New Job! Once you've secured your dream job in Data Science, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role. We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Science begins with us. CPD 100 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Aspiring data scientists looking to enter the exciting field of data science. Professionals from other disciplines who want to transition into the data science domain. Software engineers or programmers interested in expanding their skill set to include data science. Analysts or researchers who want to enhance their data analysis and modeling capabilities. Students or graduates seeking to kick-start their careers in data science with a strong foundation. Requirements No experience required. Just enrol & start learning. Career path Data Analyst: £25,000 - £55,000 per year Data Scientist: £40,000 - £85,000 per year Machine Learning Engineer: £50,000 - £100,000 per year Data Engineer: £45,000 - £80,000 per year Business Intelligence Analyst: £35,000 - £65,000 per year Data Science Manager: £70,000 - £120,000 per year. Certificates CPD Accredited e-Certificate Digital certificate - Included CPD Accredited Framed (Hardcopy) Certificate Hard copy certificate - Included Enrolment Letter Digital certificate - Included QLS Endorsed Hard Copy Certificate Hard copy certificate - Included Student ID Card Digital certificate - Included

Overview In this age of technology, data science and machine learning skills have become highly demanding skill sets. In the UK a skilled data scientist can earn around £62,000 per year. If you are aspiring for a career in the IT industry, secure these skills before you start your journey. The Complete Machine Learning & Data Science Bootcamp 2023 course can help you out. This course will introduce you to the essentials of Python. From the highly informative modules, you will learn about NumPy, Pandas and matplotlib. The course will help you grasp the skills required for using python for data analysis and visualisation. After that, you will receive step-by-step guidance on Python for machine learning. The course will then focus on the concepts of Natural Language Processing.  Upon successful completion of the course, you will receive a certificate of achievement. This certificate will help you elevate your resume. So enrol today! 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? Anyone with an interest in learning about data science can enrol in this course. It will help aspiring professionals develop the basic skills to build a promising career. Professionals already working in this can take the course to improve their skill sets. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush.   Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst Course Curriculum 18 sections • 98 lectures • 23:48:00 total length •Welcome & Course Overview6: 00:07:00 •Set-up the Environment for the Course (lecture 1): 00:09:00 •Set-up the Environment for the Course (lecture 2): 00:25:00 •Two other options to setup environment: 00:04:00 •Python data types Part 1: 00:21:00 •Python Data Types Part 2: 00:15:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1): 00:16:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2): 00:20:00 •Python Essentials Exercises Overview: 00:02:00 •Python Essentials Exercises Solutions: 00:22:00 •What is Numpy? A brief introduction and installation instructions.: 00:03:00 •NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes.: 00:28:00 •NumPy Essentials - Indexing, slicing, broadcasting & boolean masking: 00:26:00 •NumPy Essentials - Arithmetic Operations & Universal Functions: 00:07:00 •NumPy Essentials Exercises Overview: 00:02:00 •NumPy Essentials Exercises Solutions: 00:25:00 •What is pandas? A brief introduction and installation instructions.: 00:02:00 •Pandas Introduction: 00:02:00 •Pandas Essentials - Pandas Data Structures - Series: 00:20:00 •Pandas Essentials - Pandas Data Structures - DataFrame: 00:30:00 •Pandas Essentials - Handling Missing Data: 00:12:00 •Pandas Essentials - Data Wrangling - Combining, merging, joining: 00:20:00 •Pandas Essentials - Groupby: 00:10:00 •Pandas Essentials - Useful Methods and Operations: 00:26:00 •Pandas Essentials - Project 1 (Overview) Customer Purchases Data: 00:08:00 •Pandas Essentials - Project 1 (Solutions) Customer Purchases Data: 00:31:00 •Pandas Essentials - Project 2 (Overview) Chicago Payroll Data: 00:04:00 •Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data: 00:18:00 •Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach: 00:13:00 •Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials - Exercises Overview: 00:06:00 •Matplotlib Essentials - Exercises Solutions: 00:21:00 •Seaborn - Introduction & Installation: 00:04:00 •Seaborn - Distribution Plots: 00:25:00 •Seaborn - Categorical Plots (Part 1): 00:21:00 •Seaborn - Categorical Plots (Part 2): 00:16:00 •Seborn-Axis Grids: 00:25:00 •Seaborn - Matrix Plots: 00:13:00 •Seaborn - Regression Plots: 00:11:00 •Seaborn - Controlling Figure Aesthetics: 00:10:00 •Seaborn - Exercises Overview: 00:04:00 •Seaborn - Exercise Solutions: 00:19:00 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1): 00:19:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2): 00:14:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview): 00:11:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions): 00:17:00 •Project 1 - Oil vs Banks Stock Price during recession (Overview): 00:15:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3): 00:17:00 •Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview): 00:03:00 •Introduction to ML - What, Why and Types..: 00:15:00 •Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff: 00:15:00 •scikit-learn - Linear Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Linear Regression Model Hands-on (Part 2): 00:19:00 •Good to know! How to save and load your trained Machine Learning Model!: 00:01:00 •scikit-learn - Linear Regression Model (Insurance Data Project Overview): 00:08:00 •scikit-learn - Linear Regression Model (Insurance Data Project Solutions): 00:30:00 •Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc.: 00:10:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 2): 00:20:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 3): 00:11:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Overview): 00:05:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Solutions): 00:15:00 •Theory: K Nearest Neighbors, Curse of dimensionality .: 00:08:00 •scikit-learn - K Nearest Neighbors - Hands-on: 00:25:00 •scikt-learn - K Nearest Neighbors (Project Overview): 00:04:00 •scikit-learn - K Nearest Neighbors (Project Solutions): 00:14:00 •Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging.: 00:18:00 •scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1): 00:19:00 •scikit-learn - Decision Tree and Random Forests (Project Overview): 00:05:00 •scikit-learn - Decision Tree and Random Forests (Project Solutions): 00:15:00 •Support Vector Machines (SVMs) - (Theory Lecture): 00:07:00 •scikit-learn - Support Vector Machines - Hands-on (SVMs): 00:30:00 •scikit-learn - Support Vector Machines (Project 1 Overview): 00:07:00 •scikit-learn - Support Vector Machines (Project 1 Solutions): 00:20:00 •scikit-learn - Support Vector Machines (Optional Project 2 - Overview): 00:02:00 •Theory: K Means Clustering, Elbow method.: 00:11:00 •scikit-learn - K Means Clustering - Hands-on: 00:23:00 •scikit-learn - K Means Clustering (Project Overview): 00:07:00 •scikit-learn - K Means Clustering (Project Solutions): 00:22:00 •Theory: Principal Component Analysis (PCA): 00:09:00 •scikit-learn - Principal Component Analysis (PCA) - Hands-on: 00:22:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Overview): 00:02:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Solutions): 00:17:00 •Theory: Recommender Systems their Types and Importance: 00:06:00 •Python for Recommender Systems - Hands-on (Part 1): 00:18:00 •Python for Recommender Systems - - Hands-on (Part 2): 00:19:00 •Natural Language Processing (NLP) - (Theory Lecture): 00:13:00 •NLTK - NLP-Challenges, Data Sources, Data Processing ..: 00:13:00 •NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing: 00:19:00 •NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW.: 00:19:00 •NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes : 00:13:00 •NLTK - NLP - Pipeline feature to assemble several steps for cross-validation: 00:09:00