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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.

Welcome to this beginner's level course on Microsoft SQL Servers. Understand the concepts of SQL and learn to create a new database and table to perform various operations on it, with live running queries as examples. Work on hands-on exercises and understand database concepts in a real-world scenario.

Overview Become an expert in online marketing and learn how to turn brands and businesses into huge successes overnight. This popular Digital Marketing and Advertising Level 3 course is designed to teach anyone the fundamental knowledge needed to perform dynamic online advertising that works. The many online learning modules provide expert tuition for every aspect of Digital Marketing; from using SEO to target an audience, to utilising the power of social media to make a product go viral. You will also be taught how to use video and email marketing in order to maximise the recognition for your work and make everyone aware of your product. 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 Digital Marketing and Advertising Level 3. It is available to all students, of all academic backgrounds. Requirements Our Digital Marketing and Advertising Level 3 is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 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 13 sections • 123 lectures • 11:23:00 total length •Welcome: 00:01:00 •How to register your company: 00:04:00 •How to see Email Sender's Company and Logo in Your Gmail: 00:02:00 •How to Generate sitemap of a website: 00:03:00 •How to protect a website from Spam on WordPress: 00:02:00 •Quick way to identify whether the website is Mobile optimized: 00:03:00 •How to identify registration data of website: 00:01:00 •How to identify duplicate content from the web: 00:03:00 •How to create google alerts: 00:03:00 •How to find the age of the domin: 00:02:00 •How to check if the website server is down: 00:01:00 •How to create text notes thatwill self destruct after being read: 00:02:00 •How to send google search information to your friends: 00:03:00 •How to find webhost of any website: 00:02:00 •Discover new sites that are similar to what you like alredy: 00:03:00 •How to easily highlight the important parts of a web page: 00:01:00 •How to share you email online without worrying about spam: 00:02:00 •How to get compute level answers without searching: 00:03:00 •The easiest way to setup email reminders: 00:03:00 •How to find the original URL tht's hiding behind a short URL: 00:02:00 •How to corrupt a file you shared online: 00:01:00 •How to create a throwaway email: 00:02:00 •How to check if your email account has been compromised: 00:01:00 •How to register website on Google search console: 00:06:00 •How to Optimize your website homepage: 00:06:00 •How to add a sitemap on google search: 00:07:00 •How to shortlist targeted keyword list in google keyword planner: 00:08:00 •How to set international targeting on google search: 00:02:00 •How to remove a URL from google search engine: 00:03:00 •How to identify competitors keyword: 00:08:00 •How to leverage top sites to get on google search results: 00:04:00 •Discover powerful data analytics to mesure SEO performance: 00:06:00 •How to do keyword research: 00:11:00 •How to write perfect title tags for search engines: 00:05:00 •How to optimise heading tags, external and internal links: 00:08:00 •What are backlinks & how to get them: 00:06:00 •How to write a perfect Meta description: 00:06:00 •How to enhance speed & performance of your website: 00:04:00 •Youtube account setup: 00:04:00 •Account optimization: 00:09:00 •How to create & setup Youtube channel banner: 00:05:00 •Youtube channel tags, thumbnails & custom thumbnails: 00:08:00 •Analyse Youtube keyword research: 00:05:00 •Youtube SEO techniques: 00:07:00 •What are Youtube cards & how does it work: 00:06:00 •How to optimise comments & reply them in bulk: 00:03:00 •How to grow your channel with competitor Analysis: 00:07:00 •How to manage multiple YouTube accounts: 00:02:00 •A simple yet powerful trick to increase your subscribers list: 00:03:00 •Youtube Paid Advertising: 00:13:00 •How to monetise your YouTube channel: 00:02:00 •What are Google Ads & how does it work: 00:16:00 •Account setup: 00:04:00 •Competitors analysis: 00:08:00 •Campaign types & how to select the right campaign: 00:07:00 •Bids & Budgets: 00:08:00 •How to target the right audience: 00:07:00 •Google Ads advance campaign settings: 00:07:00 •Choosing the right keywords: 00:05:00 •How to write ads that gets more clicks: 00:06:00 •How to install tracking code on your website: 00:04:00 •How to add filters & remove internal traffic: 00:04:00 •How to track paid campaigns: 00:04:00 •How to look and analyse different segment data: 00:06:00 •How to configure goals in google analysics: 00:05:00 •How to link google Adwords account: 00:03:00 •How to manage multiple analytics accounts: 00:02:00 •How to remove spam traffic: 00:04:00 •Email marketing tools set up ( Mailchimp and Gestresponse): 00:10:00 •How to install signup or popup forms on the website: 00:17:00 •How to collect email address without a wbsite: 00:05:00 •How to create a 'Hook' to your signup forms: 00:08:00 •Discover the psychology behind acquiring more leads: 00:09:00 •Email marketing automation process: 00:08:00 •Email analytics: 00:07:00 •How to increase your connections in no time: 00:08:00 •Secret of LinkedIn InMails: 00:05:00 •Discover the best ways to use Linkedin Groups: 00:09:00 •How to setup a company page on Linkedin: 00:04:00 •How to increase traffic to your website using Linkedin blog: 00:07:00 •Twitter Account setup: 00:03:00 •Knowing Twitter features: 00:06:00 •Following twitter accounts: 00:03:00 •Twitter profile optimisation: 00:06:00 •How to get Twitter followers: 00:10:00 •Posting first 5 tweets for engagement: 00:05:00 •Leveraging Hashtags to increase your tweets visibility: 00:04:00 •What are twitter polls & how do you use them: 00:05:00 •A powerful trick to acquire customers on twitter: 00:03:00 •How to get followers retweet your post: 00:03:00 •How to embed a twitter button to your website or post: 00:02:00 •Twitter analytics: 00:04:00 •Set your Facebook page: 00:05:00 •Facebook Icon, cover image & description: 00:06:00 •How to get your first page likes: 00:08:00 •Discover how to increase your page likes: 00:02:00 •How to manage multiple Facebook page: 00:03:00 •Facebook comments: 00:05:00 •Leveraging Facebook groups: 00:05:00 •Facebook Autoposting: 00:04:00 •Run a competition: 00:06:00 •Facebook Ads: 00:04:00 •How to get best out of Facebook: 00:15:00 •Facebook pixel & Re-marketing: 00:04:00 •How to setup a Instagram business profile: 00:07:00 •Set up Instagram bio & profile image: 00:03:00 •Leveraging Instagram accounts: 00:06:00 •A simple way to create free content on Instagram: 00:05:00 •Secret of hashtags on Instagram: 00:04:00 •Reposting Instagram App: 00:04:00 •How to get genuine Instagram followers: 00:05:00 •Discover how to grow your business through Instagram stories: 00:05:00 •How to get your posts reposted on Instgram by influncers: 00:05:00 •A quick way to do App store marketing research: 00:16:00 •How to discover the estimate size of your market: 00:08:00 •Discover the best ways to promote your app: 00:15:00 •App installs via Facebook Ads: 00:16:00 •App installs via Google Ads: 00:14:00 •How to make money from your app: 00:08:00 •How to optimise your App store listing ?: 00:14:00 •Discover growth hacking techniques for App downloads: 00:09:00 •Techniques to get to the top of App store ranking: 00:07:00 •Assignment - Digital Marketing and Advertising Level 3: 00:00:00

Digital marketing is not just a "secure" professional route in today's economy, but it is also a flourishing employment market! Digital marketing is a terrific option because the need for it is growing every day in the UK. Companies used to promote on television, radio, and in newspapers, but now they are more focused on advertising on digital media. This course will get you up and running quickly in gaining the fundamental skills and training needed to establish your career as a digital marketer. Digital Skills: Digital Marketing is the best digital marketing course for people who want to learn how to leverage social media and popular online apps to increase product and service recognition. You'll be led through real-world instances and methods, as well as learning activities designed to help you create extremely successful commercials. After completing this course, you will be able to develop and execute first-rate marketing campaigns utilising email, SEO, and a variety of other tactics. This knowledge will be important for your CV when applying for senior positions in this industry. After this course, you will be able to: Learn the fundamentals of SEO Improve your understanding of Google AdWords and Google Analytics Learn efficient Facebook marketing strategies Learn about lead-creation tactics Discover the fundamentals of email marketing Learn about the Content Management System (CMS) Develop your knowledge of strategic marketing, sales growth, and other areas Discover the ideal step-by-step LinkedIn marketing strategy Learn how to create Instagram leads Discover how they increased their internet sales Learn how much money to put into internet marketing Discover how to boost their conversion rate and convert website visitors into paying clients Learn how Google, Facebook, Amazon, and other online "monsters" employ internet marketing methods Discover how to use a list-building method Why Prefer this Digital Skills: Digital Marketing Course? Opportunity to earn a certificate accredited by CPD after completing this course Student ID card with amazing discounts - completely for FREE! (£10 postal charges will be applicable for international delivery) Standards-aligned lesson planning Innovative and engaging content and activities Assessments that measure higher-level thinking and skills Complete the program in your own time, at your own pace Each of our students gets full 24/7 tutor support Experts created the Digital Skills: Digital Marketing course to provide a rich and in-depth training experience for all students who enrol in it. Enrol in the course right now and you'll have immediate access to all of the course materials. Then, from any internet-enabled device, access the course materials and learn when it's convenient for you. Start your learning journey straight away with this course and take a step toward a brighter future! *** Course Curriculum *** Here is the curriculum breakdown of the course: Module 01: Introduction This module covers the following topics: Welcome Module 02: General Tips & Tricks Series This module covers the following topics: How to register your company How to see Email Sender's Company and Logo in Your Gmail How to Generate a sitemap of a website How to protect a website from Spam on WordPress Quick way to identify whether the website is Mobile optimized How to identify registration data of website How to identify duplicate content from the web How to create google alerts How to find the age of the domain How to check if the website server is down How to create text notes that will self destruct after being read How to send google search information to your friends How to find webhost of any website Discover new sites that are similar to what you like alredy How to easily highlight the important parts of a web page How to share you email online without worrying about spam How to get compute level answers without searching The easiest way to setup email reminders How to find the original URL tht's hiding behind a short URL How to corrupt a file you shared online How to create a throwaway email How to check if your email account has been compromised Module 03: SEO (Search Engine Optimisation) This module covers the following topics: How to register website on Google search console How to Optimize your website homepage How to add a sitemap on google search How to shortlist targeted keyword list in google keyword planner How to set international targeting on google search How to remove a URL from google search engine How to identify competitors keyword How to leverage top sites to get on google search results Discover powerful data analytics to mesure SEO performance How to do keyword research How to write perfect title tags for search engines How to optimise heading tags, external and internal links What are backlinks & how to get them How to write a perfect Meta description How to enhance speed & performance of your website Module 04: YouTube This module covers the following topics: Youtube account setup Account optimization How to create & setup Youtube channel banner Youtube channel tags, thumbnails & custom thumbnails Analyse Youtube keyword research Youtube SEO techniques What are Youtube cards & how does it work How to optimise comments & reply them in bulk How to grow your channel with competitor Analysis How to manage multiple YouTube accounts A simple yet powerful trick to increase your subscribers list Youtube Paid Advertising How to monetise your YouTube channel Module 05: Google AdWords This module covers the following topics: What are Google Ads & how does it work Account setup Competitors analysis Campaign types & how to select the right campaign Bids & Budgets How to target the right audience Google Ads advance campaign settings Choosing the right keywords How to write ads that gets more clicks Module 06: Google Analytics This module covers the following topics: How to install tracking code on your website How to add filters & remove internal traffic How to track paid campaigns How to look and analyse different segment data How to configure goals in google analysics How to link google Adwords account How to manage multiple analytics accounts How to remove spam traffic Module 07: Email Marketing This module covers the following topics: Email marketing tools set up ( Mailchimp and Gestresponse) How to install signup or popup forms on the website How to collect email address without a wbsite How to create a 'Hook' to your signup forms Discover the psychology behind acquiring more leads Email marketing automation process Email analytics Module 08: Linkedln This module covers the following topics: How to increase your connections in no time Secret of LinkedIn InMails Discover the best ways to use Linkedin Groups How to setup a company page on Linkedin How to increase traffic to your website using Linkedin blog Module 09: Twitter This module covers the following topics: Twitter Account setup Knowing Twitter features Following twitter accounts Twitter profile optimisation How to get Twitter followers Posting first 5 tweets for engagement Leveraging Hashtags to increase your tweets visibility What are twitter polls & how do you use them A powerful trick to acquire customers on twitter How to get followers retweet your post How to embed a twitter button to your website or post Twitter analytics Module 10: Facebook This module covers the following topics: Set your Facebook page Facebook Icon, cover image & description How to get your first page likes Discover how to increase your page likes How to manage multiple Facebook page Facebook comments Leveraging Facebook groups Facebook Autoposting Run a competition Facebook Ads How to get best out of Facebook Facebook pixel & Re-marketing Module 11: Instagram This module covers the following topics: How to setup a Instagram business profile Set up Instagram bio & profile image Leveraging Instagram accounts A simple way to create free content on Instagram Secret of hashtags on Instagram Reposting Instagram App How to get genuine Instagram followers Discover how to grow your business through Instagram stories How to get your posts reposted on Instgram by influncers Module 12: Mobile App This module covers the following topics: A quick way to do App store marketing research How to discover the estimate size of your market Discover the best ways to promote your app App installs via Facebook Ads App installs via Google Ads How to make money from your app How to optimise your App store listing ? Discover growth hacking techniques for App downloads Techniques to get to the top of App store ranking CPD 15 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Digital Skills: Digital Marketing course is suitable for: Individuals who are seeking to acquire digital marketing skills and knowledge Professionals who want to improve their digital marketing skills Business owners who want to learn how to market their business online Individuals who are interested in pursuing a career in digital marketing Professionals who are looking to improve their digital marketing skills for career advancement or to increase their employability Entrepreneurs and small business owners who want to learn how to promote their products or services online effectively Marketing or business students looking to expand their skill set and stay up-to-date with the latest digital marketing trends and tools Non-marketing professionals who want to learn digital marketing skills to improve their job prospects or add value to their current role Requirements The program does not require any prior knowledge; everyone may participate! This course is open to anyone interested in learning from anywhere in the world. Every student must be over the age of 16 and have a passion for learning and literacy. This 100% online course can be accessed from any internet-connected device, such as a computer, tablet, or smartphone. This Digital Skills: Digital Marketing course allows you to study at your speed and grow a quality skillset. Career path Marketing Executive (£20,000 to £50,000) Advertisers (£20,000 to £80,000) Market Researcher (£17,000 to £24,000) Advertising Media Buyer (£21,000 to £36,000) Brand Manager (£27,000 to £65,000) Advertising Media Planner (£18,000 to £50,000) Certificates CPD Accredited Certificate Digital certificate - £10 CPD Accredited Certificate Hard copy certificate - £29 If you are an international student, then you have to pay an additional 10 GBP as an international delivery charge.

Embark on a transformative journey with the 'CompTIA CySA+ Cybersecurity Analyst Course,' designed to fortify the digital frontiers of business. This comprehensive training program begins with an immersive introduction to the cybersecurity realm, setting the stage for a deep dive into the sophisticated world of threat data and intelligence. With an emphasis on real-world application, participants will gain invaluable insights into organizational security, developing the acumen to anticipate, identify, and neutralize digital threats. Mastery over vulnerability assessment tools and mitigation strategies forms the bedrock of this curriculum, providing learners with a robust skill set pivotal for the modern cybersecurity landscape. Learning Outcomes Interpret threat data to reinforce organizational security frameworks. Assess vulnerabilities using state-of-the-art tools and methodologies. Apply best practices for ensuring software and hardware assurance. Analyze security solutions for robust infrastructure management. Implement and manage incident response protocols to address potential compromises effectively. Why choose this CompTIA CySA+ Cybersecurity Analyst Course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the CompTIA CySA+ Cybersecurity Analyst Course 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. Who is this CompTIA CySA+ Cybersecurity Analyst Course for? Individuals aiming to specialize in cybersecurity analysis. IT professionals seeking to broaden their cybersecurity knowledge. Organizational staff responsible for managing digital security risks. Security consultants requiring up-to-date threat intelligence expertise. System administrators looking to implement enhanced security measures. Career path Cybersecurity Analyst - £25,000 to £60,000 Vulnerability Analyst - £30,000 to £65,000 Security Operations Centre (SOC) Analyst - £32,000 to £70,000 Incident Responder - £27,000 to £68,000 Digital Forensics Specialist - £35,000 to £75,000 Information Security Consultant - £40,000 to £80,000 Prerequisites This CompTIA CySA+ Cybersecurity Analyst Course does not require you to have any prior qualifications or experience. You can just enrol and start learning.This CompTIA CySA+ Cybersecurity Analyst Course 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. Course Curriculum Section 01: Introduction Introduction 00:02:00 All about the Exam 00:08:00 What's New on the CompTIA CySA+ Exam? 00:05:00 Meet the Instructors 00:02:00 Thinking like the Enemy 00:09:00 Section 02: The Importance of Threat Data and Intelligence Intelligence Sources and Confidence Levels 00:08:00 Threat Indicators and Actors 00:08:00 Threat Trends 00:07:00 Intelligence Cycle and ISACs 00:06:00 Section 03: Threat Intelligence in Support of Organizational Security Attack Frameworks 00:06:00 Threat Research 00:11:00 Threat Modeling and Intelligence Sharing 00:06:00 Section 04: Vulnerability Assessment Tools Vulnerability Identification 00:07:00 Scanning Parameters and Criteria 00:09:00 Scanning Special Considerations 00:06:00 Validation 00:03:00 Remediation and Mitigation 00:08:00 Inhibitors to Remediation 00:07:00 Section 05: Threats and Vulnerabilities Associated with Specialized Technology Web Applications Scanners, Part 1 00:10:00 Web Applications Scanners, Part 2 00:05:00 Scanning 00:06:00 Configuring and Executing Scans 00:08:00 Vulnerability Scanning 00:10:00 Reverse Engineering 00:08:00 Enumeration 00:06:00 Wireless Assessment Tools 00:08:00 Cloud Assessment Tools 00:04:00 Section 06: Threats and Vulnerabilities Associated with Specialized Technology Mobile and IoT 00:10:00 Embedded and Firmware Systems (RTOS, SoC, and FPGA) 00:09:00 Access and Vehicles Risk 00:08:00 Automation and Control Risk 00:10:00 Section 07: Threats and Vulnerabilities Associated with Operating in the Cloud Cloud Models 00:07:00 Remote Service Invocation (FaaS, IaC, API) 00:10:00 Cloud Vulnerabilities 00:06:00 Section 08: Mitigating Controls for Attacks and Software Vulnerabilities Injection and Overflow Attacks 00:09:00 Authentication Attacks 00:07:00 Exploits 00:08:00 Application Vulnerabilities, Part 1 00:08:00 Application Vulnerabilities, Part 2 00:07:00 Section 09: Security Solutions for Infrastructure Management Network Architecture and Asset Management 00:09:00 Protecting Your Territory 00:05:00 Identity and Access Management 00:11:00 Encryption and Active Defense 00:08:00 Section 10: Software Assurance Best Practices Platforms 00:07:00 SOA and DevSecOps 00:09:00 Secure Software Development 00:08:00 Best Coding Practices 00:04:00 Section 11: Hardware Assurance Best Practices Trusted Hardware 00:10:00 Hardware Encryption 00:04:00 Hardware Security 00:08:00 Section 12: Data Analysis in Security Monitoring Activities Data Analytics 00:10:00 Endpoint Security 00:08:00 Recon Results, Part 1 00:13:00 Recon Results, Part 2 00:05:00 Impact Analysis 00:05:00 Collective Tools 00:09:00 Query Writing 00:07:00 E-mail Analysis, Part 1 00:10:00 E-mail Analysis, Part 2 00:08:00 Section 13: Implement Configuration Changes to Existing Controls to Improve Security Permissions 00:09:00 Firewalls 00:08:00 Intrusion Prevention Rules 00:05:00 DLP and Endpoint Detection 00:05:00 Section 14: The Importance of Proactive Threat Hunting Threat Hunting and the Hypothesis 00:06:00 Threat Hunting Process 00:07:00 Results and Benefits 00:05:00 Section 15: Compare and Contrast Automation Concepts and Technologies Workflow and Scripting 00:07:00 API and Malware Signature Creation 00:08:00 Threat Feeds and Machine Learning 00:06:00 Protocols, Standards, and Software Engineering 00:05:00 Section 16: The Importance of the Incident Response Process IR Roles and Responsibilities 00:08:00 IR Active Preparation 00:10:00 Section 17: Appropriate Incident Response Procedures Incident Response Process 00:07:00 Section 18: Analyze Potential Indicators of Compromise Network Symptoms 00:04:00 Host Symptoms 00:08:00 Application Symptoms 00:04:00 Section 19: Utilize Basic Digital Forensics Techniques Digital Forensics 00:10:00 Seizure and Acquisitions 00:05:00 Forensics Acquisition Tools 00:09:00 Mobile, Virtualization, and Cloud 00:06:00 Forensics Analysis, Part 1 00:04:00 Forensics Analysis, Part 2 00:08:00 Packet Capture 00:12:00 Section 20: The Importance of Data Privacy and Protection Data Privacy and Security 00:06:00 Nontechnical Controls 00:09:00 Technical Controls 00:08:00 Section 21: Security Concepts in Support of Organizational Risk Mitigation Business Impact Analysis 00:05:00 Risk Identification 00:05:00 Risk Calculation and Communication 00:06:00 Training 00:04:00 Supply Chain Assessment 00:04:00 Section 22: The Importance of Frameworks, Policies, Procedures, and Controls Frameworks 00:13:00 Policies and Procedures 00:05:00 Controls and Procedures 00:08:00 Verification 00:06:00 Assignment Assignment - CompTIA CySA+ Cybersecurity Analyst Course 00:00:00

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Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the SQL NoSQL Big Data and Hadoop, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Course Content Section 01: Introduction Introduction 00:07:00 Building a Data-driven Organization - Introduction 00:04:00 Data Engineering 00:06:00 Learning Environment & Course Material 00:04:00 Movielens Dataset 00:03:00 Section 02: Relational Database Systems Introduction to Relational Databases 00:09:00 SQL 00:05:00 Movielens Relational Model 00:15:00 Movielens Relational Model: Normalization vs Denormalization 00:16:00 MySQL 00:05:00 Movielens in MySQL: Database import 00:06:00 OLTP in RDBMS: CRUD Applications 00:17:00 Indexes 00:16:00 Data Warehousing 00:15:00 Analytical Processing 00:17:00 Transaction Logs 00:06:00 Relational Databases - Wrap Up 00:03:00 Section 03: Database Classification Distributed Databases 00:07:00 CAP Theorem 00:10:00 BASE 00:07:00 Other Classifications 00:07:00 Section 04: Key-Value Store Introduction to KV Stores 00:02:00 Redis 00:04:00 Install Redis 00:07:00 Time Complexity of Algorithm 00:05:00 Data Structures in Redis : Key & String 00:20:00 Data Structures in Redis II : Hash & List 00:18:00 Data structures in Redis III : Set & Sorted Set 00:21:00 Data structures in Redis IV : Geo & HyperLogLog 00:11:00 Data structures in Redis V : Pubsub & Transaction 00:08:00 Modelling Movielens in Redis 00:11:00 Redis Example in Application 00:29:00 KV Stores: Wrap Up 00:02:00 Section 05: Document-Oriented Databases Introduction to Document-Oriented Databases 00:05:00 MongoDB 00:04:00 MongoDB Installation 00:02:00 Movielens in MongoDB 00:13:00 Movielens in MongoDB: Normalization vs Denormalization 00:11:00 Movielens in MongoDB: Implementation 00:10:00 CRUD Operations in MongoDB 00:13:00 Indexes 00:16:00 MongoDB Aggregation Query - MapReduce function 00:09:00 MongoDB Aggregation Query - Aggregation Framework 00:16:00 Demo: MySQL vs MongoDB. Modeling with Spark 00:02:00 Document Stores: Wrap Up 00:03:00 Section 06: Search Engines Introduction to Search Engine Stores 00:05:00 Elasticsearch 00:09:00 Basic Terms Concepts and Description 00:13:00 Movielens in Elastisearch 00:12:00 CRUD in Elasticsearch 00:15:00 Search Queries in Elasticsearch 00:23:00 Aggregation Queries in Elasticsearch 00:23:00 The Elastic Stack (ELK) 00:12:00 Use case: UFO Sighting in ElasticSearch 00:29:00 Search Engines: Wrap Up 00:04:00 Section 07: Wide Column Store Introduction to Columnar databases 00:06:00 HBase 00:07:00 HBase Architecture 00:09:00 HBase Installation 00:09:00 Apache Zookeeper 00:06:00 Movielens Data in HBase 00:17:00 Performing CRUD in HBase 00:24:00 SQL on HBase - Apache Phoenix 00:14:00 SQL on HBase - Apache Phoenix - Movielens 00:10:00 Demo : GeoLife GPS Trajectories 00:02:00 Wide Column Store: Wrap Up 00:04:00 Section 08: Time Series Databases Introduction to Time Series 00:09:00 InfluxDB 00:03:00 InfluxDB Installation 00:07:00 InfluxDB Data Model 00:07:00 Data manipulation in InfluxDB 00:17:00 TICK Stack I 00:12:00 TICK Stack II 00:23:00 Time Series Databases: Wrap Up 00:04:00 Section 09: Graph Databases Introduction to Graph Databases 00:05:00 Modelling in Graph 00:14:00 Modelling Movielens as a Graph 00:10:00 Neo4J 00:04:00 Neo4J installation 00:08:00 Cypher 00:12:00 Cypher II 00:19:00 Movielens in Neo4J: Data Import 00:17:00 Movielens in Neo4J: Spring Application 00:12:00 Data Analysis in Graph Databases 00:05:00 Examples of Graph Algorithms in Neo4J 00:18:00 Graph Databases: Wrap Up 00:07:00 Section 10: Hadoop Platform Introduction to Big Data With Apache Hadoop 00:06:00 Big Data Storage in Hadoop (HDFS) 00:16:00 Big Data Processing : YARN 00:11:00 Installation 00:13:00 Data Processing in Hadoop (MapReduce) 00:14:00 Examples in MapReduce 00:25:00 Data Processing in Hadoop (Pig) 00:12:00 Examples in Pig 00:21:00 Data Processing in Hadoop (Spark) 00:23:00 Examples in Spark 00:23:00 Data Analytics with Apache Spark 00:09:00 Data Compression 00:06:00 Data serialization and storage formats 00:20:00 Hadoop: Wrap Up 00:07:00 Section 11: Big Data SQL Engines Introduction Big Data SQL Engines 00:03:00 Apache Hive 00:10:00 Apache Hive : Demonstration 00:20:00 MPP SQL-on-Hadoop: Introduction 00:03:00 Impala 00:06:00 Impala : Demonstration 00:18:00 PrestoDB 00:13:00 PrestoDB : Demonstration 00:14:00 SQL-on-Hadoop: Wrap Up 00:02:00 Section 12: Distributed Commit Log Data Architectures 00:05:00 Introduction to Distributed Commit Logs 00:07:00 Apache Kafka 00:03:00 Confluent Platform Installation 00:10:00 Data Modeling in Kafka I 00:13:00 Data Modeling in Kafka II 00:15:00 Data Generation for Testing 00:09:00 Use case: Toll fee Collection 00:04:00 Stream processing 00:11:00 Stream Processing II with Stream + Connect APIs 00:19:00 Example: Kafka Streams 00:15:00 KSQL : Streaming Processing in SQL 00:04:00 KSQL: Example 00:14:00 Demonstration: NYC Taxi and Fares 00:01:00 Streaming: Wrap Up 00:02:00 Section 13: Summary Database Polyglot 00:04:00 Extending your knowledge 00:08:00 Data Visualization 00:11:00 Building a Data-driven Organization - Conclusion 00:07:00 Conclusion 00:03:00 Resources Resources - SQL NoSQL Big Data And Hadoop 00:00:00

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Highlights of the Course Course Type: Online Learning Duration: 11 Hours 11 Minutes Tutor Support: Tutor support is included Customer Support: 24/7 customer support is available Quality Training: The course is designed by an industry expert Recognised Credential: Recognised and Valuable Certification Completion Certificate: Free Course Completion Certificate Included Instalment: 3 Installment Plan on checkout What you will learn from this course? Gain comprehensive knowledge about retail analytics and management Understand the core competencies and principles of retail analytics and management Explore the various areas of retail analytics and management Know how to apply the skills you acquired from this course in a real-life context Become a confident and expert retail manager Retail Analytics In Microsoft Excel Course Master the skills you need to propel your career forward in Microsoft excel. This course will equip you with the essential knowledge and skillset that will make you a confident office admin and take your career to the next level. This comprehensive retail analytics in Microsoft excel course is designed to help you surpass your professional goals. The skills and knowledge that you will gain through studying this retail analytics in Microsoft excel course will help you get one step closer to your professional aspirations and develop your skills for a rewarding career. This comprehensive course will teach you the theory of effective Microsoft excel practice and equip you with the essential skills, confidence and competence to assist you in the Microsoft excel industry. You'll gain a solid understanding of the core competencies required to drive a successful career in Microsoft excel. This course is designed by industry experts, so you'll gain knowledge and skills based on the latest expertise and best practices. This extensive course is designed for office admin or for people who are aspiring to specialize in Microsoft excel. Enroll in this retail analytics in Microsoft excel course today and take the next step towards your personal and professional goals. Earn industry-recognized credentials to demonstrate your new skills and add extra value to your CV that will help you outshine other candidates. Who is this Course for? This comprehensive retail analytics in Microsoft excel course is ideal for anyone wishing to boost their career profile or advance their career in this field by gaining a thorough understanding of the subject. Anyone willing to gain extensive knowledge on this Microsoft excel can also take this course. Whether you are a complete beginner or an aspiring professional, this course will provide you with the necessary skills and professional competence, and open your doors to a wide number of professions within your chosen sector. Entry Requirements This retail analytics in Microsoft excel course has no academic prerequisites and is open to students from all academic disciplines. You will, however, need a laptop, desktop, tablet, or smartphone, as well as a reliable internet connection. Assessment This retail analytics in Microsoft excel course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%. Advance Your Career This retail analytics in Microsoft excel course will provide you with a fresh opportunity to enter the relevant job market and choose your desired career path. Additionally, you will be able to advance your career, increase your level of competition in your chosen field, and highlight these skills on your resume. Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. What is CPD? Employers, professional organisations, and academic institutions all recognise CPD, therefore a credential from CPD Certification Service adds value to your professional goals and achievements. Benefits of CPD Improve your employment prospects Boost your job satisfaction Promotes career advancement Enhances your CV Provides you with a competitive edge in the job market Demonstrate your dedication Showcases your professional capabilities What is IPHM? The IPHM is an Accreditation Board that provides Training Providers with international and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation is a guarantee of quality and skill. Benefits of IPHM It will help you establish a positive reputation in your chosen field You can join a network and community of successful therapists that are dedicated to providing excellent care to their client You can flaunt this accreditation in your CV It is a worldwide recognised accreditation What is Quality Licence Scheme? This course is endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Benefits of Quality License Scheme Certificate is valuable Provides a competitive edge in your career It will make your CV stand out Course Curriculum Course Introduction Introduction 00:03:00 Part 1: Forecasting Basics of Forecasting 00:05:00 Creating Linear Model with Trendlines 00:08:00 1.1 Getting Data Ready For Regression Model Gathering Business Knowledge 00:03:00 Data Exploration 00:03:00 The Data and the Data Dictionary 00:07:00 Univariate analysis and EDD 00:03:00 Discriptive Data Analytics in Excel 00:10:00 Outlier Treatment 00:04:00 Identifying and Treating Outliers in Excel 00:04:00 Missing Value Imputation 00:03:00 Identifying and Treating missing values in Excel 00:04:00 Variable Transformation in Excel 00:03:00 Dummy variable creation: Handling qualitative data 00:04:00 Dummy Variable Creation in Excel 00:07:00 Correlation Analysis 00:09:00 Creating Correlation Matrix in Excel 00:08:00 1.2 Forecasting Using Regression Model The Problem Statement 00:01:00 Basic Equations and Ordinary Least Squares (OLS) method 00:08:00 Assessing accuracy of predicted coefficients 00:14:00 Assessing Model Accuracy: RSE and R squared 00:07:00 Creating Simple Linear Regression model 00:02:00 Multiple Linear Regression 00:05:00 The F - statistic 00:08:00 Interpreting results of Categorical variables 00:05:00 Creating Multiple Linear Regression model 00:07:00 1.3 Handling Special Events Like Holiday Sales Forecasting in presence of special events 00:02:00 Excel: Running Linear Regression using Solver 00:08:00 Excel: Including the impact of Special Events 00:22:00 1.4 Identifying Seasonality & Trend for Forecasting Models to identify Trend & Seasonality 00:06:00 Excel: Additive model to identify Trend & Seasonality 00:09:00 Excel: Multiplicative model to identify Trend & Seasonality 00:06:00 Market Basket Analysis Market Basket and Lift - Introduction 00:08:00 Named Ranges - Excel 00:10:00 Indirect Function - Excel 00:05:00 2-way lift calculation in Excel 00:11:00 2-way lift calculation - Dynamic 00:07:00 2-way lift data table creation 00:07:00 3-way lift calculation 00:19:00 Store Layout optimization using Lift values 00:15:00 RFM (Recency, Frequency, Monetary) Analysis RFM (recency, frequency, monetary) Analysis 00:08:00 RFM Analysis in Excel- Part 1 00:16:00 RFM Analysis in Excel- Part 2 00:12:00 Part 2: Pricing Part 2: Pricing Steps of setting a Pricing policy 00:03:00 Different Pricing Objectives 00:07:00 2.1 Estimating Demand Estimating Demand 00:07:00 Forms of Demand Curve 00:02:00 Excel: Estimating Linear Demand Curve 00:08:00 Excel: Estimating Power Demand curve with Elasticity 00:05:00 Excel: Estimating Power Demand Curve with points 00:03:00 Subjective Demand curve 00:01:00 Excel: Estimating Subjective Demand Curve 00:02:00 2.3 Evaluating Pricing Strategies Price Bundling 00:07:00 Types of Bundling 00:08:00 The Bundling Problem 00:04:00 Excel: Solving Bundling problem Part 1 00:14:00 Excel: Solving Bundling problem Part 2 00:08:00 Non-Linear Pricing Strategies 00:03:00 Excel: Solving Bundling problem (Price Reversal) 00:08:00 3.1 Lifetime Customer Value Lifetime Customer Value - Key concepts 00:09:00 Lifetime Customer Value - Excel model 00:11:00 3.2 Variations And Sensitivity Analysis Sensitivity Analysis in Excel 00:07:00 Variations in finding customer value 00:07:00 Appendix 1: Excel Crash Course Basics 00:08:00 Worksheet Basics 00:16:00 Entering values and Formulas 00:07:00 Data Handling Basics - Cut, Copy and Paste 00:14:00 Saving and Printing - Basics 00:09:00 Basic Formula Operations 00:13:00 Mathematical Formulas 00:19:00 Textual Formulas 00:17:00 Logical Formulas 00:11:00 Date-Time Formulas 00:07:00 Lookup Formulas ( V Lookup, Hlookup, Index-Match ) 00:08:00 Data Tools 00:19:00 Formatting data and tables 00:18:00 Pivot Tables 00:08:00 Advance Excel- Solver, Data tables 00:15:00 Assessment Assessment - Retail Analytics In Microsoft Excel 00:10:00 Certificate of Achievement Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

Learn to program with Python 3, visualize algorithms and data structures, and implement them in Python projects