1719 Analytics courses in Whetstone delivered Online

Become a META-Health professional with our 6 months intensive training! Do you want to learn the scientific background of body-mind-interactions and how to integrate this knowledge in your practical work with your clients? This course contains both self-study and live training in online classes and covers the META-Health Level 1 and 2 material. It will take 6 months including 24 live sessions, 2 hours each, mainly in a weekly rhythm. You will get preparatory videos, reading material and tasks that help to understand and integrate the content, while the group sessions focus on demonstrations, discusion of the material, and practical exercises for you. All the time, our trainers and tutors will support you and we’ll be a learning family with an active chatgroup. Altogether you should reckon approximately 5 hours per week.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for data warehouse engineers, data platform engineers, and architects and operators who build and manage data analytics pipelines. Completed either AWS Technical Essentials or Architecting on AWS Completed Building Data Lakes on AWS Overview In this course, you will learn to: Compare the features and benefits of data warehouses, data lakes, and modern data architectures Design and implement a data warehouse analytics solution Identify and apply appropriate techniques, including compression, to optimize data storage Select and deploy appropriate options to ingest, transform, and store data Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights Secure data at rest and in transit Monitor analytics workloads to identify and remediate problems Apply cost management best practices In this course, you will build a data analytics solution using Amazon Redshift, a cloud data warehouse service. The course focuses on the data collection, ingestion, cataloging, storage, and processing components of the analytics pipeline. You will learn to integrate Amazon Redshift with a data lake to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon Redshift. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Using Amazon Redshift in the Data Analytics Pipeline Why Amazon Redshift for data warehousing? Overview of Amazon Redshift Module 2: Introduction to Amazon Redshift Amazon Redshift architecture Interactive Demo 1: Touring the Amazon Redshift console Amazon Redshift features Practice Lab 1: Load and query data in an Amazon Redshift cluster Module 3: Ingestion and Storage Ingestion Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with Data API Data distribution and storage Interactive Demo 3: Analyzing semi-structured data using the SUPER data type Querying data in Amazon Redshift Practice Lab 2: Data analytics using Amazon Redshift Spectrum Module 4: Processing and Optimizing Data Data transformation Advanced querying Practice Lab 3: Data transformation and querying in Amazon Redshift Resource management Interactive Demo 4: Applying mixed workload management on Amazon Redshift Automation and optimization Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster Module 5: Security and Monitoring of Amazon Redshift Clusters Securing the Amazon Redshift cluster Monitoring and troubleshooting Amazon Redshift clusters Module 6: Designing Data Warehouse Analytics Solutions Data warehouse use case review Activity: Designing a data warehouse analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

The goal of this course is to teach you the fundamentals of Alteryx and teach you a more efficient way to clean and prepare your data. You'll learn to work with data in new ways other than Tableau and PowerBI, using Alteryx for all your data analysis needs.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced attendees who wish to learn and use basic machine learning algorithms and concepts. Students should have skills at least equivalent to the Python for Data Science courses we offer. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to Understand the main concepts and principles of predictive analytics Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects Explore advanced predictive modeling algorithms w with an emphasis on theory with intuitive explanations Learn to deploy a predictive model's results as an interactive application Learn about the stages involved in producing complete predictive analytics solutions Understand how to define a problem, propose a solution, and prepare a dataset Use visualizations to explore relationships and gain insights into the dataset Learn to build regression and classification models using scikit-learn Use Keras to build powerful neural network models that produce accurate predictions Learn to serve a model's predictions as a web application Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This course provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. Hands-on Predictive Analytics with Python is a three-day, hands-on course that guides students through a step-by-step approach to defining problems and identifying relevant data. Students will learn how to perform data preparation, explore and visualize relationships, as well as build models, tune, evaluate, and deploy models. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seabor, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. The Predictive Analytics Process Technical requirements What is predictive analytics? Reviewing important concepts of predictive analytics The predictive analytics process A quick tour of Python's data science stack Problem Understanding and Data Preparation Technical requirements Understanding the business problem and proposing a solution Practical project ? diamond prices Practical project ? credit card default Dataset Understanding ? Exploratory Data Analysis Technical requirements What is EDA? Univariate EDA Bivariate EDA Introduction to graphical multivariate EDA Predicting Numerical Values with Machine Learning Technical requirements Introduction to ML Practical considerations before modeling MLR Lasso regression KNN Training versus testing error Predicting Categories with Machine Learning Technical requirements Classification tasks Credit card default dataset Logistic regression Classification trees Random forests Training versus testing error Multiclass classification Naive Bayes classifiers Introducing Neural Nets for Predictive Analytics Technical requirements Introducing neural network models Introducing TensorFlow and Keras Regressing with neural networks Classification with neural networks The dark art of training neural networks Model Evaluation Technical requirements Evaluation of regression models Evaluation for classification models The k-fold cross-validation Model Tuning and Improving Performance Technical requirements Hyperparameter tuning Improving performance Implementing a Model with Dash Technical requirements Model communication and/or deployment phase Introducing Dash Implementing a predictive model as a web application Additional course details: Nexus Humans Hands-on Predicitive Analytics with Python (TTPS4879) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Hands-on Predicitive Analytics with Python (TTPS4879) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

With this course, you'll learn how to connect to the data source in Tableau and use Tableau for data visualization. Along the process, you'll get to grips with Tableau dashboards, explore storytelling with Tableau, and perform actions to share data with others.

You will learn about the business analysis process, from identifying business needs to assessing and prioritizing requirements. You will also gain insights into the world of business analytics, including predictive modeling and data visualization techniques that can help you turn raw data into actionable insights. Throughout the course, you will be introduced to a variety of business analysis techniques, including SWOT analysis, PEST analysis, and Porter's Five Forces framework. You will also explore different useful financial ratios that can be applied to business analysis, such as profitability ratios and liquidity ratios. This knowledge will enable you to make informed decisions and recommendations that drive business success. Finally, you will gain insights into different modern, useful tools of business analysis. From data visualization software to predictive analytics tools, you will learn how to leverage technology to enhance your business analysis capabilities and deliver value to your organization. After the successful completion of the course, you will be able to learn about the following, Understand the nature of business analysis and its role. Explain the business analysis process and business analytics. Describe different business analysis techniques. Explore different useful financial ratios applicable to business analysis. Understand different modern, useful tools of business analysis. You will learn about the business analysis process, from identifying business needs to assessing and prioritizing requirements. You will also gain insights into the world of business analytics, including predictive modeling and data visualization techniques that can help you turn raw data into actionable insights. Throughout the course, you will be introduced to a variety of business analysis techniques, including SWOT analysis, PEST analysis, and Porter's Five Forces framework. You will also explore different useful financial ratios that can be applied to business analysis, such as profitability ratios and liquidity ratios. This knowledge will enable you to make informed decisions and recommendations that drive business success. Finally, you will gain insights into different modern, useful tools of business analysis. From data visualization software to predictive analytics tools, you will learn how to leverage technology to enhance your business analysis capabilities and deliver value to your organization. VIDEO - Course Structure and Assessment Guidelines Watch this video to gain further insight. Navigating the MSBM Study Portal Watch this video to gain further insight. Interacting with Lectures/Learning Components Watch this video to gain further insight. Business Analysis Case Studies Self-paced pre-recorded learning content on this topic. Business Analysis Case Studies Put your knowledge to the test with this quiz. Read each question carefully and choose the response that you feel is correct. All MSBM courses are accredited by the relevant partners and awarding bodies. Please refer to MSBM accreditation in about us for more details. There are no strict entry requirements for this course. Work experience will be added advantage to understanding the content of the course. The certificate is designed to enhance the learner's knowledge in the field. This certificate is for everyone eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience. CEO, Director, Manager, Supervisor Business analysts Data analysts Consultants, managers. Entrepreneurs Anyone looking to gain a deeper understanding of the role of business analysis in driving business success. Average Completion Time 2 Weeks Accreditation 3 CPD Hours Level Advanced Start Time Anytime 100% Online Study online with ease. Unlimited Access 24/7 unlimited access with pre-recorded lectures. Low Fees Our fees are low and easy to pay online.

Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure. In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage. Prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - Introduction to data engineering on Azure What is data engineering Important data engineering concepts Data engineering in Microsoft Azure 2 - Introduction to Azure Data Lake Storage Gen2 Understand Azure Data Lake Storage Gen2 Enable Azure Data Lake Storage Gen2 in Azure Storage Compare Azure Data Lake Store to Azure Blob storage Understand the stages for processing big data Use Azure Data Lake Storage Gen2 in data analytics workloads 3 - Introduction to Azure Synapse Analytics What is Azure Synapse Analytics How Azure Synapse Analytics works When to use Azure Synapse Analytics 4 - Use Azure Synapse serverless SQL pool to query files in a data lake Understand Azure Synapse serverless SQL pool capabilities and use cases Query files using a serverless SQL pool Create external database objects 5 - Use Azure Synapse serverless SQL pools to transform data in a data lake Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement Encapsulate data transformations in a stored procedure Include a data transformation stored procedure in a pipeline 6 - Create a lake database in Azure Synapse Analytics Understand lake database concepts Explore database templates Create a lake database Use a lake database 7 - Analyze data with Apache Spark in Azure Synapse Analytics Get to know Apache Spark Use Spark in Azure Synapse Analytics Analyze data with Spark Visualize data with Spark 8 - Transform data with Spark in Azure Synapse Analytics Modify and save dataframes Partition data files Transform data with SQL 9 - Use Delta Lake in Azure Synapse Analytics Understand Delta Lake Create Delta Lake tables Create catalog tables Use Delta Lake with streaming data Use Delta Lake in a SQL pool 10 - Analyze data in a relational data warehouse Design a data warehouse schema Create data warehouse tables Load data warehouse tables Query a data warehouse 11 - Load data into a relational data warehouse Load staging tables Load dimension tables Load time dimension tables Load slowly changing dimensions Load fact tables Perform post load optimization 12 - Build a data pipeline in Azure Synapse Analytics Understand pipelines in Azure Synapse Analytics Create a pipeline in Azure Synapse Studio Define data flows Run a pipeline 13 - Use Spark Notebooks in an Azure Synapse Pipeline Understand Synapse Notebooks and Pipelines Use a Synapse notebook activity in a pipeline Use parameters in a notebook 14 - Plan hybrid transactional and analytical processing using Azure Synapse Analytics Understand hybrid transactional and analytical processing patterns Describe Azure Synapse Link 15 - Implement Azure Synapse Link with Azure Cosmos DB Enable Cosmos DB account to use Azure Synapse Link Create an analytical store enabled container Create a linked service for Cosmos DB Query Cosmos DB data with Spark Query Cosmos DB with Synapse SQL 16 - Implement Azure Synapse Link for SQL What is Azure Synapse Link for SQL? Configure Azure Synapse Link for Azure SQL Database Configure Azure Synapse Link for SQL Server 2022 17 - Get started with Azure Stream Analytics Understand data streams Understand event processing Understand window functions 18 - Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics Stream ingestion scenarios Configure inputs and outputs Define a query to select, filter, and aggregate data Run a job to ingest data 19 - Visualize real-time data with Azure Stream Analytics and Power BI Use a Power BI output in Azure Stream Analytics Create a query for real-time visualization Create real-time data visualizations in Power BI 20 - Introduction to Microsoft Purview What is Microsoft Purview? How Microsoft Purview works When to use Microsoft Purview 21 - Integrate Microsoft Purview and Azure Synapse Analytics Catalog Azure Synapse Analytics data assets in Microsoft Purview Connect Microsoft Purview to an Azure Synapse Analytics workspace Search a Purview catalog in Synapse Studio Track data lineage in pipelines 22 - Explore Azure Databricks Get started with Azure Databricks Identify Azure Databricks workloads Understand key concepts 23 - Use Apache Spark in Azure Databricks Get to know Spark Create a Spark cluster Use Spark in notebooks Use Spark to work with data files Visualize data 24 - Run Azure Databricks Notebooks with Azure Data Factory Understand Azure Databricks notebooks and pipelines Create a linked service for Azure Databricks Use a Notebook activity in a pipeline Use parameters in a notebook Additional course details: Nexus Humans DP-203T00 Data Engineering on Microsoft Azure training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the DP-203T00 Data Engineering on Microsoft Azure course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

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

Learn how to create and manage a successful YouTube channel for your business. This workshop will cover everything you need to know when setting up and using YouTube in your business. You will also learn how to use YouTube analytics to track your channel's performance to help you make improvements.

This Professional Certificate Course in Data Collection and Analysis offers a holistic understanding of best practices, covering digital data organization, analytics tool utilization, and effective data visualization. Participants will master strategies for collecting diverse digital channel data and gain skills in analyzing and interpreting insights for informed decision-making. After the successful completion of the course, you will be able to learn about the following: Best practices for collecting and organizing digital data How to use digital analytics tools to analyze data and gain insights Data visualization techniques and tools for presenting data effectively Strategies for collecting data from different digital channels, including social media, email, and mobile apps Best practices for analyzing and interpreting data to drive actionable insights This Professional Certificate Course in Data Collection and Analysis offers a comprehensive understanding of best practices in collecting and organizing digital data. Participants will learn to utilize digital analytics tools, master data visualization techniques, and employ strategies for collecting data from diverse digital channels, including social media and mobile apps. The course emphasizes interpreting data to derive actionable insights, empowering learners with practical skills for informed decision-making. This Professional Certificate Course in Data Collection and Analysis provides a comprehensive understanding of best practices in collecting, organizing, and analyzing digital data. Participants will learn to utilize digital analytics tools, master data visualization techniques, and develop strategies for collecting data from various digital channels, including social media and mobile apps. The course emphasizes interpreting data to derive actionable insights, empowering individuals with practical skills for informed decision-making. Course Structure and Assessment Guidelines Watch this video to gain further insight. Navigating the MSBM Study Portal Watch this video to gain further insight. Interacting with Lectures/Learning Components Watch this video to gain further insight. Data Collection and Analysis Self-paced pre-recorded learning content on this topic. Data Collection And Analysis Put your knowledge to the test with this quiz. Read each question carefully and choose the response that you feel is correct. All MSBM courses are accredited by the relevant partners and awarding bodies. Please refer to MSBM accreditation in about us for more details. There are no strict entry requirements for this course. Work experience will be added advantage to understanding the content of the course.The certificate is designed to enhance the learner's knowledge in the field. This certificate is for everyone eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience, Data Analysts and Scientists Marketing Professionals Business Intelligence Specialists Digital Marketing Managers Researchers and Academics Information Technology Professionals Decision-makers and Strategists Social Media Managers Mobile App Developers Email Marketing Specialists Average Completion Time 2 Weeks Accreditation 3 CPD Hours Level Advanced Start Time Anytime 100% Online Study online with ease. Unlimited Access 24/7 unlimited access with pre-recorded lectures. Low Fees Our fees are low and easy to pay online.