396 Courses

Become a sought-after developer with the Python Programming: 8-in-1 Premium Online Courses Bundle. Focused on key job skills including Python, Go Lang, Data Analysis, Website Development, IT, MS Excel, Problem Solving, and CSS, this bundle prepares you for multiple career paths. Employers highly value Python and Go Lang for automation and scalable applications, while Data Analysis and MS Excel boost your ability to interpret and manage complex datasets. Combine that with Website Development and CSS for attractive front-end designs, plus critical Problem Solving and IT know-how, and you become a well-rounded candidate ready to tackle real-world challenges. This is your chance to jump ahead in industries from tech startups to data analytics teams. Hurry — limited seats available! Compete High has 4.8 on 'Reviews.io' and 4.3 on Trustpilot. 🧠 Description This bundle equips you with the most sought-after skills in tech and data-driven industries. Python and Go Lang power backend logic and complex workflows, while Website Development and CSS help create engaging user interfaces. Your proficiency with Data Analysis and MS Excel opens doors to roles focused on interpreting data to drive business decisions. Strong Problem Solving skills and IT knowledge ensure you’re prepared for technical challenges employers face daily. Together, these skills give you a competitive edge for junior to mid-level roles. The bundle’s integrated approach ensures your Python, Go Lang, and Website Development abilities stand out on resumes and in interviews. ❓ FAQ Q: Who is this bundle ideal for? A: Aspiring developers, data analysts, IT professionals, and anyone looking to build solid Python and Go Lang skills combined with Website Development. Q: Will it help with data-focused roles? A: Definitely. With Data Analysis and MS Excel included, you’ll be ready for roles demanding data insight. Q: Is this bundle beginner-friendly? A: Yes, it covers foundational to intermediate skills in Python, IT, and Problem Solving.

AI in Project Management: The Next Generation of Project Decision Making Project managers need to make critical project decisions on a daily basis. They are confronted with increasing complexities, high ambiguity and the need to process an exponentially growing amount of data and information in order to make informed and good decisions. This leads to an increasing risk of project failure - meanwhile, the project management industry is already challenged with ongoing low project success rates, caused by often massive failures of projects. Project Data Analytics and Artificial Intelligence (AI) are expected to fill the gap by providing analytical and unbiased capabilities that go beyond human possibilities, towards a data-driven and fact-based decision-making approach. While there is little doubt that AI as a trending technology will disrupt the project management practice and augment today's project management capabilities, AI cannot be seen as just another new tool to make project management more effective. Rather, AI will act as a complement to human intelligence, requiring a collaborative approach and, accordingly, a significant change in project culture and peoples' mindset. Today's project decisions are usually driven by human intuition, experience, leadership, and often do not follow any rational logic. Project decision-makers will be required to abandon such an approach and shift to a data-driven, decision-making approach. This session will provide an overview of the expected changes from AI-driven project management, the resulting impact on project decision making and changes in project culture, and what actions can be taken by project professionals to match their beliefs and behaviours with the new project culture. Learning goals: Gain insights into how AI for project management will significantly change decision-making in projects Gain an understanding of how to transition to a new AI-powered project culture

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Architects and operators who build and manage data analytics pipelines 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 batch data 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 learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks 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 EMR. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Introduction to Amazon EMR Using Amazon EMR in analytics solutions Amazon EMR cluster architecture Interactive Demo 1: Launching an Amazon EMR cluster Cost management strategies Module 2: Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage Storage optimization with Amazon EMR Data ingestion techniques Module 3: High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR Apache Spark on Amazon EMR use cases Why Apache Spark on Amazon EMR Spark concepts Interactive Demo 2: Connect to an EMR cluster and perform Scala commands using the Spark shell Transformation, processing, and analytics Using notebooks with Amazon EMR Practice Lab 1: Low-latency data analytics using Apache Spark on Amazon EMR Module 4: Processing and Analyzing Batch Data with Amazon EMR and Apache Hive Using Amazon EMR with Hive to process batch data Transformation, processing, and analytics Practice Lab 2: Batch data processing using Amazon EMR with Hive Introduction to Apache HBase on Amazon EMR Module 5: Serverless Data Processing Serverless data processing, transformation, and analytics Using AWS Glue with Amazon EMR workloads Practice Lab 3: Orchestrate data processing in Spark using AWS Step Functions Module 6: Security and Monitoring of Amazon EMR Clusters Securing EMR clusters Interactive Demo 3: Client-side encryption with EMRFS Monitoring and troubleshooting Amazon EMR clusters Demo: Reviewing Apache Spark cluster history Module 7: Designing Batch Data Analytics Solutions Batch data analytics use cases Activity: Designing a batch data analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization. Overview After completing this course delegates will be capable of writing effective R code to manipulate, analyse and visualise data to enable their organisations make better, data-driven decisions. This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualisation in R. Course Outline Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. The R programming language is one of the most powerful and flexible tools in the data analytics toolkit. This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualisation in R. Mastery of these techniques will allow delegates to immediately add value in their work place by extracting valuable insight from company data to allow better, data-driven decisions. The course will explore the following topics through a series of interactive workshop sessions: What is R? Basic R programming conventions Data structures in R Accessing data in R Descriptive statistics in R Statistical analysis in R Data manipulation in R Data visualisation in R Additional course details: Nexus Humans Beginning Data Analytics With R 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 Beginning Data Analytics With R 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.

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

Step confidently into the world of financial careers with the Diploma in Accounting and Business Finance Mini Bundle. Whether you're job-hunting for entry-level finance roles or aiming to move up in corporate management, this bundle is designed to make you hireable in record time. With essential career-building keywords like Finance, Financial Analysis, Business Management, Tax, and Data Analytics with Tableau, this package puts you on every recruiter’s radar. Tailored for job relevance and maximum value, this bundle is your professional fast track into a finance-driven future—before the competition even logs in. Description Every role in today’s business ecosystem touches Finance. That’s why this bundle starts strong and stays relevant. From Finance fundamentals to advanced Financial Analysis, employers are actively seeking candidates with exactly this combination of knowledge and keywords. In industries like banking, accounting, and consultancy, Financial Analysis and Business Management appear on almost every job listing. Tax is another standout—its relevance spans every sector from SMEs to multinational corporations. It’s a high-trust area where your credibility is key, and having Tax on your CV makes your profile instantly more credible. Then there’s Data Analytics with Tableau, a career-defining keyword for any finance or business applicant. Data Analytics with Tableau gives you an edge in reporting, strategy, and decision support—skills now required in virtually every department. When you combine Finance, Financial Analysis, Business Management, Tax, and Data Analytics with Tableau in one affordable, compact bundle, you’re not just learning—you’re future-proofing your career. Miss this bundle, and you may be missing the job that could have changed everything. FAQ Q: What kinds of jobs does this bundle prepare me for? A: Junior Accountant, Finance Assistant, Business Analyst, Tax Assistant, Data Analyst, and Management Trainee. Q: Is Financial Analysis really a job skill? A: Yes—Financial Analysis is a core competency in finance and investment roles. Q: Why is Data Analytics with Tableau included? A: It’s one of the top tools used in business reporting and finance decision-making. Q: Will Business Management make me more promotable? A: Absolutely—Business Management is valued in leadership and team supervision roles. Q: What sectors use Tax skills? A: All of them—from retail and healthcare to tech, government, and finance. Q: Can I get hired without prior experience? A: Yes. The combination of Finance, Financial Analysis, Business Management, Tax, and Data Analytics with Tableau is ideal for first-time applicants and career changers. Q: Is this recognised by employers? A: These are five of the most searched keywords on CVs across UK job boards. Q: Is it good value? A: It's exceptional. You’re getting career-relevant training in five critical fields—at the cost of a single course.

Overview With the ever-increasing demand for Big Data Analytics in personal & professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in Big Data Analytics may be. Learning about Big Data Analytics or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in Big Data Analytics . That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on Big Data Analytics is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates. The self-paced online learning methodology by compete high in this Big Data Analytics course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course! Instead of searching for hours, enrol right away on this Big Data Analytics course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run. Who is this course for? While we refrain from discouraging anyone wanting to do this Big Data Analytics course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it: Anyone looking for the basics of Big Data Analytics , Jobseekers in the relevant domains, Anyone with a ground knowledge/intermediate expertise in Big Data Analytics , Anyone looking for a certificate of completion on doing an online training on this topic, Students of Big Data Analytics , or anyone with an academic knowledge gap to bridge, Anyone with a general interest/curiosity Career Path This Big Data Analytics course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams.     Course Curriculum Module 1_ Introduction to Big Data. Introduction to Big Data. 00:00 Module 2_ Hadoop and MapReduce. Hadoop and MapReduce. 00:00 Module 3_ NoSQL Databases. NoSQL Databases. 00:00 Module 4_ Data Storage and Retrieval. Data Storage and Retrieval. 00:00 Module 5_ Data Processing with Spark. Data Processing with Spark. 00:00 Module 6_ Data Analysis with Hadoop and Pig. Data Analysis with Hadoop and Pig. 00:00

Boost your insurance career with payroll, Excel, accounting, data entry, and Tableau-led data analytics skills. Navigating the corporate side of UK insurance requires more than just policy talk. This mini bundle neatly ties together the essentials—think payroll, accounting, data entry, Excel, and Tableau. Whether you’re brushing up your spreadsheets or deciphering financials, you’ll gain the structured knowledge to operate with precision. From managing numbers to visualising them, this collection delivers the core knowledge behind successful insurance operations. It’s designed for those who want to make insurance sound less... dull. (It’s not. There are spreadsheets. They're thrilling.) All courses are online, self-paced, and geared to help you move confidently through the essentials of corporate insurance functions. Learning Outcomes: Understand payroll functions within a corporate insurance context. Explore accounting processes used across insurance firms. Input, organise and manage insurance data accurately. Use Excel for reporting and insurance data management tasks. Visualise data clearly using Tableau’s dashboard features. Identify ways to optimise internal insurance operations with data. Who Is This Course For: Staff in insurance admin or back-office support roles. Payroll clerks needing sector-specific understanding. Accounting assistants in the insurance sector. Excel users looking to manage data more efficiently. Those moving into data-based insurance roles. Data entry professionals in insurance firms. Business support staff in insurance environments. Team leaders needing digital insurance fluency. Career Path (UK Average Salaries): Insurance Administrator – £24,000 per year Payroll Officer – £28,000 per year Data Entry Clerk – £21,500 per year Accounts Assistant – £26,000 per year Excel Data Analyst – £30,000 per year Tableau Reporting Analyst – £35,000 per year

Data Analysis (Beginner): Data Analysis Course Online Are you trying to get the knowledge and abilities required to excel in data analysis at the beginner level? Our Data Analysis Course (Beginner) could be your perfect option for this. The Data Analysis Course (Beginner) offers comprehensive training in data analysis methodologies and tools. The Data Analysis Course (Beginner) covers topics such as data cleaning, visualisation, and statistical analysis. Also, the Data Analysis Course (Beginner) teaches programming in Python or R. Moreover, the Data Analysis Course (Beginner) equips students with essential skills for deriving insights from data. This Data Analysis Course (Beginner) explains data manipulation and interpretation. Enrol in our Data Analysis Course (Beginner) to prepare them for careers in data analysis across various industries. Main Course: Data Analytics Course (Beginner) [ Note: Free PDF certificate as soon as completing the Data Analysis (Beginner): Data Analysis Course] Data Analysis (Beginner): Data Analysis Course This Data Analysis (Beginner): Data Analysis Training Course consists of 12 modules. Who is this course for? Data Analysis (Beginner): Data Analysis Course This Data Analysis (Beginner): Data Analysis Course is recommended for anyone looking to advance in their data analysis career. Requirements Data Analysis (Beginner): Data Analysis Course To enrol in this Data Analysis (Beginner): Data Analysis Course, students must fulfil the following requirements: Data Analysis: Good Command over English language is mandatory to enrol in our Data Analysis Course. Data Analysis: Be energetic and self-motivated to complete our Data Analysis Course. Data Analysis: Basic computer Skill is required to complete our Data Analysis Course. Data Analysis: If you want to enrol in our Data Analysis Course, you must be at least 15 years old. Career path Data Analysis (Beginner): Data Analysis Course The Data Analysis (Beginner): Data Analysis Course opens up a wide range of work prospects, especially in the UK labour market.

Course Overview This comprehensive Data Analytics course provides an in-depth exploration of data analysis, covering the essential principles and techniques used to extract valuable insights from data. Learners will engage with core concepts, such as data mining, statistical analysis, and visualisation, enabling them to make informed decisions and drive business outcomes. By the end of the course, participants will have the skills to analyse and interpret data, apply analytical tools effectively, and present their findings clearly. This course equips learners with the necessary tools to understand and leverage data in various professional settings, adding significant value to their career prospects. Course Description The Data Analytics course covers a wide range of topics, including the fundamentals of data analysis, statistical methods, and various data visualisation techniques. Learners will explore essential tools such as Excel and specialised software, while gaining a deep understanding of how to collect, store, and process data effectively. Emphasis is placed on developing the analytical mindset required to interpret data accurately and draw actionable insights. This course is designed to ensure learners can confidently navigate the world of data analytics and apply their knowledge in diverse industries, enhancing their problem-solving and decision-making abilities. Course Modules Module 01: Introduction to the World of Data Module 02: Basics of Data Analytics Module 03: Statistics for Data Analytics Module 04: Actions Taken in the Data Analysis Process Module 05: Gathering the Right Information Module 06: Storing Data Module 07: Data Mining Module 08: Excel for Data Analytics Module 09: Tools for Data Analytics Module 10: Data-Analytic Thinking Module 11: Data Visualisation That Clearly Describes Insights Module 12: Data Visualisation Tools (See full curriculum) Who is this course for? Individuals seeking to enhance their analytical skills for data-driven decision-making. Professionals aiming to transition into data analytics or enhance their data-related roles. Beginners with an interest in understanding data and its applications across industries. Business professionals seeking to leverage data for strategic growth. Career Path Data Analyst Business Intelligence Analyst Data Scientist Market Research Analyst Operations Analyst Financial Analyst Business Analyst Data Visualisation Specialist