30 Predictive Analytics courses delivered Online

QLS Endorsed + CPD QS Accredited - Dual Certification | Instant Access | 24/7 Tutor Support | All-Inclusive Cost

Unlock the potential of business intelligence with our specialized Business Intelligence Analyst Course. Learn to analyze data, extract insights, and drive strategic decisions to optimize business performance. Gain practical skills in data visualization, reporting, and predictive analytics using industry-leading tools and techniques. Whether you're a business professional or aspiring analyst, this course equips you with the expertise to excel in leveraging data for business intelligence.

Sales Overview: Roadway/Highway Design and Engineering Software Are you ready to revolutionize your roadway and highway projects? Introducing our comprehensive Roadway/Highway Design and Engineering software, meticulously crafted to streamline every aspect of your design process. From initial conceptualization to final construction, our software offers a suite of modules tailored to meet the diverse needs of modern transportation infrastructure projects. 1. Introduction To Roadway/Highway Design and Engineering: Kickstart your projects with a solid foundation in roadway and highway design principles. Our software provides an intuitive introduction module, offering users a clear understanding of the fundamentals essential for successful project execution. With interactive tutorials and detailed resources, users can quickly familiarize themselves with industry best practices and regulatory requirements. 2. Geometric Design of Roadways/Highways: Efficient and safe roadway geometry is paramount to any transportation project. Our software's Geometric Design module empowers engineers to create optimal road alignments, intersections, and transitions with precision and ease. Through advanced algorithms and customizable parameters, users can simulate various design scenarios to achieve optimal traffic flow and safety standards. 3. Pavement Design for Roadways/Highways: Ensure the longevity and performance of your road surfaces with our Pavement Design module. Tailored to accommodate diverse traffic loads and environmental conditions, our software offers state-of-the-art pavement analysis tools. From flexible to rigid pavements, our algorithms optimize material selection and thickness design, empowering engineers to deliver sustainable infrastructure solutions. 4. Drainage Design for Roadways/Highways: Combat water accumulation and mitigate flood risks with our Drainage Design module. Our software integrates hydraulic modeling and stormwater management techniques to design efficient drainage systems for roadways and highways. With intuitive interfaces and predictive analysis capabilities, engineers can confidently implement drainage solutions that meet regulatory standards and minimize environmental impact. 5. Materials and Construction: Seamlessly transition from design to construction with our Materials and Construction module. Access a comprehensive database of construction materials and techniques, complete with cost estimations and procurement guidelines. Whether it's asphalt mixes or bridge components, our software empowers project stakeholders to make informed decisions and optimize construction processes for efficiency and quality. 6. Environmental Considerations in Roadway/Highway Design and Engineering: Embrace sustainability and environmental stewardship in every phase of your project with our Environmental Considerations module. From ecological impact assessments to carbon footprint analyses, our software equips engineers with the tools to minimize environmental disturbances and enhance project sustainability. With built-in compliance checks and mitigation strategies, users can navigate regulatory requirements with confidence while preserving natural resources. Experience the future of roadway and highway design with our cutting-edge software solution. Empower your team to deliver innovative infrastructure projects that prioritize safety, efficiency, and sustainability. Contact us today to learn more about how our Roadway/Highway Design and Engineering software can elevate your projects to new heights. Course Curriculum Module 1: Introduction To Roadway/Highway Design and Engineering Introduction To Roadway/Highway Design and Engineering 00:00 Module 2: Geometric Design of Roadways/Highways Geometric Design of Roadways/Highways 00:00 Module 3: Pavement Design for Roadways/Highways Pavement Design for Roadways/Highways 00:00 Module 4: Drainage Design for Roadways/Highways Drainage Design for Roadways/Highways 00:00 Module 5: Materials and Construction Materials and Construction 00:00 Module 6: Environmental Considerations in Roadway/Highway Design and Engineering Environmental Considerations in Roadway/Highway Design and Engineering 00:00

As the retail industry continues to evolve, the demand for skilled data analysts is on the rise. According to recent statistics, the global retail analytics market is expected to reach $10.4 billion by 2025, with a compound annual growth rate of 19.6%. This indicates a significant opportunity for professionals in this field. Our Data Analyst: Retail Data Analytics course offers comprehensive training in the latest techniques and tools used in the retail industry, equipping learners with the skills they need to succeed in this exciting and growing field. This Diploma in Retail And Data Analytics at QLS Level 5 course is endorsed by The Quality Licence Scheme and accredited by CPDQS (with 150 CPD points)to make your skill development & career progression more accessible than ever! At the end of this Data Analyst : Retail Data Analytics course, you will: Understand the basics of retail analytics and how it impacts the industry Analyse retail psychology and apply it in different scenarios Develop a retail strategy that aligns with business goals Create effective forecasts to plan and manage inventory Set appropriate pricing strategies that balance profit and customer satisfaction Apply analytics software to derive insights from data and inform decision-making Streamline supply chain management to improve efficiency and reduce costs Understand the sales process and how to engage with customers at the checkout Develop strategies for selling in multiple channels, including e-commerce Use trends and customer data to target effectively and increase sales This Retail Data Analytics at QLS Level 5 training can help you to accomplish your ambitions and prepare you for a meaningful career. So, join us today and gear up for excellence! Why Prefer This Data Analyst : Retail Data Analytics at QLS Level 5 Course? Opportunity to earn a certificate endorsed by the Quality Licence Scheme & another accredited by CPDQS which is completely free. Get a free student ID card! (£10 postal charge will be applicable for international delivery) Innovative and engaging content. Free assessments 24/7 tutor support. Take a step toward a brighter future! *** Course Curriculum *** Here is the curriculum breakdown of the Retail Data Analytics at QLS Level 5 course: Module 1: Introduction To Retail Analytics Module 2: Retail Psychology Module 3: Retail And Data Analytics Module 4: Benefits Of Retail Analytics Module 5: Retail Strategy Module 6: Retail Buying And Merchandising Module 7: Forecasting Module 8: Retail Pricing Module 9: Analytics Software Module 10: Supply Chain Management In Retailing Module 11: The Sales Process And Dealing With Customers At The Checkout Module 12: Selling In Multiple Channels Module 13: Taking Trends And Targeting Customers Effectively Assessment Process You have to complete the assignment questions given at the end of the course and score a minimum of 60% to pass each exam. Our expert trainers will assess your assignment and give you feedback after you submit the assignment. You will be entitled to claim a certificate endorsed by the Quality Licence Scheme after you have completed all of the Diploma in Retail And Data Analytics at QLS Level 5 exams. CPD 150 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Aspiring data analysts seeking to specialise in the retail industry Retail professionals who wish to develop their analytical skills and knowledge Business owners and entrepreneurs looking to improve their retail operations Requirements No prior background or expertise is required. Career path Data Analyst: Average salary of £32,000 per annum Pricing Analyst: Average salary of £30,000 per annum Supply Chain Analyst: Average salary of £29,000 per annum Forecasting Analyst: Average salary of £31,000 per annum E-commerce Analyst: Average salary of £32,000 per annum Certificates CPDQS Accredited Certificate Digital certificate - Included Diploma in Retail And Data Analytics at QLS Level 5 Hard copy certificate - Included Show off Your New Skills with a Certificate of Completion After successfully completing the Diploma in Retail And Data Analytics at QLS Level 5, you can order an original hardcopy certificate of achievement endorsed by the Quality Licence Scheme andalso you can order CPDQSAccredited Certificate that is recognised all over the UK and also internationally. The certificates will be home-delivered, completely free of cost.

Get detailed customer behaviour insights and know-how to measure the return on investment across various retail business aspects by enrolling in our Retail and Data Analytics course. Based on a set of Retail Management principles, this exclusive learning package mentors you to excel in Retail and Data Analytics to convey its benefits to your retail business and prepare yourself for future opportunities and challenges. Retail and Data Analytics training focuses on sales, inventory, productivity, customers, and many crucial business operation aspects. After your successful completion, you'll be far more capable of dealing with product efficiency complications, communicating with the reputed Retail Organizations, delivering improved customer service to lure more people on the door and much more. Enrol today and find smart ways to make your prospects feel comfortable. Learning outcomes Get introduced to retail and data analytics Learn to convert insights into profits Learn how actually to use reusable bags and seats. Read up on compromise price effect Understand the left digit effect Learn the concept of treasure hunt Use data to find new micro-markets Gain the knowledge on competitor threat analytics Know the hardcore terms Know the tracking effectiveness of celebrity marketing. Recognize the benefits of real analytics Certificate of Achievement Endorsed Certificate of Achievement from the Quality Licence Scheme Once the course has been completed and the assessment has been passed, all students are entitled to receive an endorsed certificate. This will provide proof that you have completed your training objectives, and each endorsed certificate can be ordered and delivered to your address for only £99. Please note that overseas students may be charged an additional £10 for postage. CPD Certificate of Achievement from Janets Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Endorsement This course and/or training programme has been endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. This course and/or training programme is not regulated by Ofqual and is not an accredited qualification. Your training provider will be able to advise you on any further recognition, for example progression routes into further and/or higher education. For further information please visit the Learner FAQs on the Quality Licence Scheme website. Method of Assessment In order to ensure the Quality Licensing scheme endorsed and CPD acknowledged certificate, learners need to score at least 60% pass marks on the assessment process. After submitting assignments, our expert tutors will evaluate the assignments and give feedback based on the performance. After passing the assessment, one can apply for a certificate. Who is This Course for? This course is intended to teach individuals all the required aspects of Retail and Data Analytics and the ability to provide contingency and recovery plans for a high-performing organisation or business. Requirements The Retail and Data Analytics is open to all students and has no formal entry requirements. To study the Retail and Data Analytics, 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. Career Path This course is intended for those wanting to work in an operational or support area and take responsibility for identifying risk-related issues. As such, it covers the following careers and roles: Retail Financial Analyst Insights Analyst Retail Junior Retail Sales Analyst Retail Category Finance Analyst Test Analyst- eCommerce Transformation-Retail Insight Analyst Application Support Analyst Contract Business Analyst Course Content Module 1: Introduction to Retail Analytics Introduction to Retail Analytics 00:50:00 Module 2: Retail Psychology Retail Psychology 00:15:00 Module 3: Retail and Data Analytics Retail and Data Analytics 00:18:00 Module 4: Benefits of Retail Analytics Benefits of Retail Analytics 00:25:00 Module 5: Retail Strategy Retail Strategy 00:15:00 Module 6: Retail Buying and Merchandising Retail Buying and Merchandising 00:19:00 Module 7: Forecasting Forecasting 00:35:00 Module 8: Retail Pricing Retail Pricing 00:34:00 Module 9: Analytics Software Analytics Software 00:34:00 Module 10: Supply Chain Management in Retailing Supply Chain Management in Retailing 00:14:00 Module 11: The Sales Process and Dealing with Customers at the Checkout The Sales Process and Dealing with Customers at the Checkout 00:12:00 Module 12: Selling in Multiple Channels Selling in Multiple Channels 00:23:00 Module 13: Taking Trends and Targeting Customers Effectively Taking Trends and Targeting Customers Effectively 00:13:00 Assignment Assignment - Retail And Data Analytics 2 weeks, 1 day Order Your Certificate Order your Certificate QLS 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

Duration 3 Days 18 CPD hours This course is intended for Business application consultant Data Consultant / Manager Database Administrator Application developer BI specialist Overview This course will prepare you to: Understand and put into practice the main advanced modeling capabilities of SAP HANA 2.0 SPS04 in the areas of text search and analysis, graph modeling, spatial analysis and predictive modeling. Promote these advanced modeling capabilities to extend the core SAP HANA Modeling features. Broaden your experience with the modern SAP HANA tooling in XS Advanced (SAP Web IDE for SAP HANA) This course provides advanced knowledge and practical experience on several topics that are included in, or connected to, the scope of the modeler role. Its purpose is to take a step further, beyond the core modeling knowledge from HA300, and to demonstrate how applications powered by SAP HANA can benefit from innovations such as Spatial Data Storage and Processing, Text Search and Analysis, Predictive Analysis and Graph Modeling.The course is supported by many demos and exercise, which demonstrate the advanced modeling capabilities in several scenarios. For example, working with classical schemas or HDI containers in XS Advanced, using the SQL console, developing graphical models. Some of the proposed case studies blend together several modeling capabilities, such as text with spatial, or text with graph.An introduction to SAP HANA Series Data is also provided. Introduction to Advanced ModelingSAP HANA Predictive Analysis Library (PAL) Describing SAP HANA PAL Using PAL in Flowgraphs Calling PAL Functions in Calculation Views Calling PAL Procedures in SQL Scripts Exploring the PAL Library SAP HANA Spatial Introducing SAP HANA Spatial Working with Spatial Data Types Importing and Exporting Spatial Data Accessing and Manipulating Spatial Data Using Spatial Clustering SAP HANA Graph Defining SAP HANA Graph Workspace Describing the Different Graph Algorithms Using the Graph Node in Calculation Views Using GraphScript Procedures SAP HANA Text Understanding Full Text Search Understanding Text Analysis Understanding Text Mining SAP HANA Series Data Getting Started with SAP HANA Series Data

Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course are Application Consultants, Business Analysts, Business Process Owners/Team Leads/Power Users, Solution Architects, and System Architects. Overview Describe the SAP BusinessObjects Business Intelligence tools.Learn about the use cases and get an overview of basic functions of the most important BusinessObjects reporting tools. In this course, students describe the SAP BusinessObjects Business Intelligence tools and learn about the use cases by getting an overview of basic functions of the most important BusinessObjects reporting tools. Overview of SAP BusinessObjects Business Intelligence (BI) 4.1 Describing SAP Analytics Solutions Identifying the Components of SAP BusinessObjects 4.1 Semantic Layer in SAP BusinessObjects BI 4.1 Describing Semantic Layer Technology Creating a Universe in the Information Design Tool SAP Crystal Reports Creating a Report in SAP Crystal Reports for Enterprise Creating a Report in SAP Crystal Reports 2013 Differentiating SAP Crystal Reports 2013 and SAP Crystal Reports for Enterprise SAP BusinessObjects Web Intelligence Creating Web Intelligence Documents in SAP BusinessObjects Web Intelligence SAP BusinessObjects Analysis, Edition for Microsoft Office Creating a Workbook in SAP BusinessObjects Analysis, Edition for Microsoft Office SAP BusinessObjects Analysis, Edition for OLAP Creating a Workspace with SAP BusinessObjects Analysis, Edition for OLAP SAP BusinessObjects Design Studio 1.2 Creating an Analytical Application in SAP BusinessObjects Design Studio 1.2 SAP BusinessObjects Dashboards Creating a Dashboard with SAP BusinessObjects Dashboards SAP BusinessObjects Explorer Creating an SAP BusinessObjects Explorer Information Space SAP Lumira and SAP Predictive Analysis Visualizing Data in SAP Lumira Forecasting in SAP Predictive Analysis Additional course details: Nexus Humans SAPBI Introduction to SAP BusinessObjects BI Solutions 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 SAPBI Introduction to SAP BusinessObjects BI Solutions 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 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 2 Days 12 CPD hours This course is intended for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful. Overview By the end of this course, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from data. This course is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You?ll discover how to tune the algorithms to provide the best predictions on new and unseen data. As you delve into later sections, you?ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. Data Exploration and Cleaning Python and the Anaconda Package Management System Different Types of Data Science Problems Loading the Case Study Data with Jupyter and pandas Data Quality Assurance and Exploration Exploring the Financial History Features in the Dataset Activity 1: Exploring Remaining Financial Features in the Dataset Introduction to Scikit-Learn and Model Evaluation Introduction Model Performance Metrics for Binary Classification Activity 2: Performing Logistic Regression with a New Feature and Creating a Precision-Recall Curve Details of Logistic Regression and Feature Exploration Introduction Examining the Relationships between Features and the Response Univariate Feature Selection: What It Does and Doesn't Do Building Cloud-Native Applications Activity 3: Fitting a Logistic Regression Model and Directly Using the Coefficients The Bias-Variance Trade-off Introduction Estimating the Coefficients and Intercepts of Logistic Regression Cross Validation: Choosing the Regularization Parameter and Other Hyperparameters Activity 4: Cross-Validation and Feature Engineering with the Case Study Data Decision Trees and Random Forests Introduction Decision trees Random Forests: Ensembles of Decision Trees Activity 5: Cross-Validation Grid Search with Random Forest Imputation of Missing Data, Financial Analysis, and Delivery to Client Introduction Review of Modeling Results Dealing with Missing Data: Imputation Strategies Activity 6: Deriving Financial Insights Final Thoughts on Delivering the Predictive Model to the Client

Duration 3 Days 18 CPD hours This course is intended for Before taking this course delegates should already be familiar with basic analytics techniques, comfortable with basic data manipulation tools such as spreadsheets and databases and already familiar with at least one programming language Overview This course teaches delegates who are already familiar with analytics techniques and at least one programming language how to effectively use the programming language for three tasks: data manipulation and preparation, statistical analysis and advanced analytics (including predictive modelling and segmentation). 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. Outcomes: After completing the course, delegates will be capable of writing production-ready R code to perform advanced analytics tasks enabling their organisations make better, data-driven decisions. Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. Topic 1 Intro to our chosen language Topic 2 Basic programming conventions Topic 3 Data structures Topic 4 Accessing data Topic 5 Descriptive statistics Topic 6 Data visualisation Topic 7 Statistical analysis Topic 8 Advanced data manipulation Topic 9 Advanced analytics ? predictive modelling Topic 10 Advanced analytics ? segmentation