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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.
This course offers you the exact skills and principles you need to deliver a project using Python along with the tools you can use to create solid Python code. Master the language constructs, tools, and terminology with this carefully designed course for beginners.
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(£10 postal charges will be applicable for international delivery) Standard-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 tutor support on weekdays (Monday to Friday) Diploma in Accountancy at QLS Level 5 Module 01: Introduction to Accounting What Is Accounting? Accounting and Bookkeeping Who Uses Accounting Information? Accountability in Accounting Financial Statements How Different Business Entities Present Accounting Information Module 02: The Role of an Accountant What Is an Accountant? Roles and Responsibilities Important Skills Accounting Automation Transparency and Security Data Analysis Module 03: Accounting Concepts and Standards Introduction to Accounting Concepts Introduction to Accounting Standards Accounting Standards in the UK International Standards International Financial Reporting Standards Module 04: Double-Entry Bookkeeping Introduction of Double-Entry Bookkeeping What Does the Account Show? Account NameDebits and CreditsAccount Details Rules for Double-Entry Transactions Inventory Double-Entry Transactions for Inventory Returns of Inventory Drawings Income and Expenses How Many Different Expense Accounts Should Be Opened? Balancing Accounts General Rules for Balancing Accounts Module 05: Balance Sheet Introduction of Balance Sheet The Components of a Balance Sheet AssetsLiabilitiesNet Worth or Equity The Equation Understanding the Balance Sheet What Does the Date on the Balance Sheet Mean? Module 06: Income statement Understanding the Income Statement The Accrual Concept Revenue Expenses Net Income Interest and Income Taxes Bad Debt Expense Module 07: Financial Statements Introduction of Financial Statements Trial Balance Statement of Comprehensive Income Calculation of Profit Difference between Gross and Net Profits Trading Account Profit and Loss Account Statement of Financial Position Non-Current AssetsCurrent AssetsCurrent LiabilitiesNon-Current LiabilitiesCapital Module 08: Cash Flow Statements What Is a Statement of Cash Flows? What Is the Purpose of the Cash Flow Statement? Cash and Cash Equivalents Operating Activities Investing Activities Financing Activities Module 09: Understanding Profit and Loss Statement Introduction of Profit and Loss Account Measurement of Income Relation Between Profit and Loss Account and Balance Sheet Preparation of Profit and Loss Account Module 10: Financial Budgeting and Planning What Is a Budget? Planning and Control Advantages of Budgeting Developing the Profit Strategy and Budgeted Profit and Loss Statement Budgeting Cash Flow from Profit for the Coming Year Capital Budgeting Module 11: Auditing What Is an Audit? Types of Audits External AuditsInternal AuditsInternal Revenue Service (IRS) Audits Why Audits? Who's Who in the World of Audits What's in an Auditor's Report Assessment Process We offer an integrated assessment framework to make the process of evaluation and accreditation for learners easier. 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 exams. CPD 150 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Is This Course Right for You? Anyone interested in learning more about this subject should take this course. This course will help you grasp the basic concepts as well as develop a thorough understanding of the subject. All are welcome to take this course. There are no prerequisites for enrollment, and you can access the course materials from any location in the world. This course is preferable for people who want to pursue a career in Aspiring Accountant Recent Graduates Individuals interested in building a career in this sector Individuals working in the relevant field Professionals who have rooms to improve skills and knowledge Requirements This course does not require any prior knowledge; everyone may participate! This course is open to anyone who is 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. 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The certificate will be home-delivered, with a pricing scheme of - 119 GBP inside the UK 129 GBP (including postal fees) for international delivery CPD Accredited Certificate 29 GBP for Printed Hardcopy Certificate inside the UK 39 GBP for Printed Hardcopy Certificate outside the UK (international delivery)
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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) Globally accepted standard structured 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 Anti-Money Laundering? 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 Anti-Money Laundering? course materials. Then, from any internet-enabled device, access the Anti-Money Laundering? course materials and learn when it's convenient for you. Start your learning journey straight away with this Anti-Money Laundering? course and take a step toward a brighter future! *** Course Curriculum *** Here are the topics you will cover on the Course: >> Anti Money Laundering (AML) Course << Module 01: Introduction to Money Laundering Module 02: Proceeds of Crime Act 2002 Module 03: Development of Anti-Money Laundering Regulation Module 04: Responsibility of the Money Laundering Reporting Officer Module 05: Risk-based Approach Module 06: Customer Due Diligence Module 07: Record Keeping Module 08: Suspicious Conduct and Transactions Module 09: Awareness and Training Here is the module breakdown of Anti Money Laundering (AML) Course ----------- Module 01: Introduction to Money Laundering What Is Money Laundering? Turning 'Bad' Money into 'Legitimate' Money How Is Money Laundered? Why Are AML Efforts Important? The Three Stages of Money Laundering Module 02: Proceeds of Crime Act 2002 Introduction The Principal Offences Contained in Part 7 of POCA 2002 The Notion of Criminal Property Elements of Criminal Property The Concept of Knowledge The Notion of Suspicion Module 03: Development of Anti-Money Laundering Regulation Introduction The First Money Laundering Directive Terrorism legislation The Proceeds of Crime Act 2002 and Serious Organised Crime and money laundering offences under the Police Act 2005 The Second Money Laundering Directive The Third Money Laundering Directive The Fourth Money Laundering Directive The Fifth Money Laundering Directive Module 04: Responsibility of the Money Laundering Reporting Officer What Is a Money Laundering Reporting Officer? Who Can be Appointed as an MLRO? The Role of The Money Laundering Reporting Officer Module 05: Risk-based Approach Introduction What Is a Risk-Based Approach (RBA)? A Risk-Based Approach to Customer Due Diligence (CDD) How to Assess the Risk Profile of The Entity How to Assess Client Risk Conducting the Client Risk Assessment Module 06: Customer Due Diligence What is Customer Due Diligence? Main Elements of a Customer Due Diligence Program Enhanced Due Diligence Enhanced Due Diligence for Higher-Risk Customers Account Opening, Customer Identification and Verification Consolidated Customer Due Diligence Module 07: Record Keeping The Purpose of Record-Keeping What Records Have to be Kept? Customer Identification In What Form Should Records be Kept? Failure to Keep Records Module 08: Suspicious Conduct and Transactions What Is Suspicious Activity? What Is a Suspicious Transaction? Avoiding a National Reporting or Record-Keeping Requirement Wire or Fund Transfers Insufficient or Suspicious Information by a Customer Other Suspicious Customer Activity The Identification of Unusual Transactions The Types of Events That Might Cause Suspicion Module 09: Awareness and Training The Importance of Staff Awareness and Training The Core Obligations of Training Legal and Regulatory Obligations Staff Responsibilities Internal Training Procedures Assessment Process Once you have completed all the modules in the Anti Money Laundering course, you can assess your skills and knowledge with an optional assignment. Our expert trainers will assess your assignment and give you feedback afterwards. Showcase Your Accomplishment of New Skills: Get a Certification of Completion The learners have to successfully complete the assessment of this Anti Money Laundering course to achieve the CPD accredited certificate. Digital certificates can be ordered for only £10. The learner can purchase printed hard copies inside the UK for £29, and international students can purchase printed hard copies for £39. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Is This Anti Money Laundering (AML) Course Right for You? This Anti Money Laundering course has a practical focus and is open to anyone interested in the subject. However, the course is preferable by: Individuals with specific anti-money laundering duties Individuals working in financial services who want a thorough understanding of anti-money laundering Anyone who aspires to a career in anti-money laundering or fraud prevention Requirements Enrol on the Anti Money Laundering with no formal entry requirements! If you have a passion for knowledge and want to learn something new, register on the Anti Money Laundering without any delay. We only ask that all students have a passion for learning and literacy, and be over the age of 16. Complete the Anti Money Laundering online from your computer, tablet, or smartphone, and learn in a way that suits you. Career path Enrolling on this Anti Money Laundering Course can lead you to the following career paths: Ethics & Compliance Officer Lawyer Entrepreneur AML Analyst Accountant Bookkeeper Chartered Accountant Money Laundering Reporting Officer AML Officer Business Analyst Compliance Manager And many more!
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Highlights of the Course Course Type: Online Learning Duration: 8 Hours 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 psychology Understand the core competencies and principles of psychology Explore the various areas of psychology Know how to apply the skills you acquired from this course in a real-life context Become a confident and expert psychologist Psychology - Advance Training Course Online Course Master the skills you need to propel your career forward in child psychology. This course will equip you with the essential knowledge and skillset that will make you a confident psychologist and take your career to the next level. This comprehensive psychology course is designed to help you surpass your professional goals. The skills and knowledge that you will gain through studying this psychology 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 child psychology practice and equip you with the essential skills, confidence and competence to assist you in the child psychology industry. You'll gain a solid understanding of the core competencies required to drive a successful career in child psychology. 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 psychologist or for people who are aspiring to specialise in child psychology. Enrol in this psychology course today and take the next step towards your personal and professional goals. Earn industry-recognised 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 psychology 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 child psychology 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 psychology 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 psychology 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 psychology 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. Course Curriculum Perspectives in Psychology What Is Psychology 00:07:00 The Biological Approach 00:10:00 Behaviourist And Cognitive Approaches 00:09:00 Person-Centred Approaches 00:08:00 Debates In Psychology 00:12:00 Social Psychology Social Influence: Compliance, Obedience and Conformity 00:10:00 Social Cognition 00:08:00 Applied Social Psychology 00:09:00 Cognitive Psychology and Its Applications Perception 00:09:00 Attention 00:07:00 Remembering (Memory) 00:09:00 Research Methods In Psychology 00:12:00 Forgetting (Memory) 00:07:00 Language 00:10:00 Thinking (Cognition) 00:07:00 Attitudes 00:09:00 Problem-Solving And Artificial Intelligence 00:09:00 Child Development Issues In Child Development 00:05:00 Cognitive Development 00:06:00 The Development Of Language And Communication 00:06:00 Social Perception (Interpersonal Perception) 00:05:00 Moral Development 00:09:00 The Psychology of Atypical (Abnormal) Behaviour The Definition And Diagnosis Of Atypical (Abnormal) Behaviour 00:06:00 Treatments Of Atypical (Abnormal) Behaviour 00:07:00 Emotional Disorders 00:05:00 Research Methods Research Methods 00:06:00 Research Issues 00:06:00 Data Analysis 00:06:00 Thank You and Good Bye! 00:02:00 Child Psychology Introduction About your tutor 00:01:00 About the course 00:02:00 Child Psychology - Applied What is 'Child Psychology'? 00:08:00 The Role of Child Psychologist 00:06:00 Where do Child Psychologists Work 00:06:00 Child Psychology - Theoretical Approach Why do we need to learn theories? 00:08:00 Developmental Theories: What we are born with 00:09:00 Developmental Theories: How environment impacts us 00:09:00 Environmental & Socio-Cultural Factors in Development 'Attachment' factor in newborns 00:08:00 Socio-Cultural Factors in Child's Development 00:07:00 Family & Schooling Factors in Development The Role of Parenting in Child's Development 00:10:00 Relationship Breakdown in the Family 00:07:00 Schooling Environment 00:08:00 Counselling Young Children 00:08:00 Cognitive and Emotional Development Language & Cognitive Development 00:07:00 Emotions & Feelings 00:06:00 Socialising with others 00:04:00 Thank You and Good Bye!44 00:01:00 Addiction Psychology Introduction: About instructor & the course 00:02:00 Theories of Addiction The Moral Model 00:05:00 The Psychological Model 00:06:00 The Medical / Disease Model 00:09:00 The Socio-Cultural Model 00:05:00 Addiction Treatments Pharmacotherapy 00:03:00 The Minnesota Model 00:04:00 Counselling and Therapy 00:07:00 Harm Reduction Model 00:04:00 Treatments in Practice 00:05:00 Addiction in Society Drug policies, Legislation and Decriminalisation 00:08:00 Community change, Outreach, Harm Reduction or Abstinence 00:06:00 Alcohol and Drug education 00:05:00 Alcohol- and drug related issues in the workplace 00:06:00 Addiction in Families Codependency, Children of alcoholic families, parenting styles, family factors 00:08:00 Relapse for families, 'letting go', dependent attitudes and dependent behaviours 00:04:00 Al-Anon 00:04:00 The Intervention Approach3 00:04:00 Working with Addiction Why be a 'helper' 00:03:00 'Helper' qualities and attitudes 00:03:00 Counselling / 'helping' skills 00:04:00 Obtain Your Certificate Order Your Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00
Duration 5 Days 30 CPD hours This course is intended for This intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers who want to leverage Scala and Spark to tackle complex data challenges and develop scalable, high-performance applications across diverse domains. Practical programming experience is required to participate in the hands-on labs. Overview Working in a hands-on learning environment led by our expert instructor you'll: Develop a basic understanding of Scala and Apache Spark fundamentals, enabling you to confidently create scalable and high-performance applications. Learn how to process large datasets efficiently, helping you handle complex data challenges and make data-driven decisions. Gain hands-on experience with real-time data streaming, allowing you to manage and analyze data as it flows into your applications. Acquire practical knowledge of machine learning algorithms using Spark MLlib, empowering you to create intelligent applications and uncover hidden insights. Master graph processing with GraphX, enabling you to analyze and visualize complex relationships in your data. Discover generative AI technologies using GPT with Spark and Scala, opening up new possibilities for automating content generation and enhancing data analysis. Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.Guided by our expert instructor, you?ll explore the fundamentals of Scala programming and Apache Spark while gaining valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You?ll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems. Introduction to Scala Brief history and motivation Differences between Scala and Java Basic Scala syntax and constructs Scala's functional programming features Introduction to Apache Spark Overview and history Spark components and architecture Spark ecosystem Comparing Spark with other big data frameworks Basics of Spark Programming SparkContext and SparkSession Resilient Distributed Datasets (RDDs) Transformations and Actions Working with DataFrames Spark SQL and Data Sources Spark SQL library and its advantages Structured and semi-structured data sources Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.) Data manipulation using SQL queries Basic RDD Operations Creating and manipulating RDDs Common transformations and actions on RDDs Working with key-value data Basic DataFrame and Dataset Operations Creating and manipulating DataFrames and Datasets Column operations and functions Filtering, sorting, and aggregating data Introduction to Spark Streaming Overview of Spark Streaming Discretized Stream (DStream) operations Windowed operations and stateful processing Performance Optimization Basics Best practices for efficient Spark code Broadcast variables and accumulators Monitoring Spark applications Integrating External Libraries and Tools, Spark Streaming Using popular external libraries, such as Hadoop and HBase Integrating with cloud platforms: AWS, Azure, GCP Connecting to data storage systems: HDFS, S3, Cassandra, etc. Introduction to Machine Learning Basics Overview of machine learning Supervised and unsupervised learning Common algorithms and use cases Introduction to Spark MLlib Overview of Spark MLlib MLlib's algorithms and utilities Data preparation and feature extraction Linear Regression and Classification Linear regression algorithm Logistic regression for classification Model evaluation and performance metrics Clustering Algorithms Overview of clustering algorithms K-means clustering Model evaluation and performance metrics Collaborative Filtering and Recommendation Systems Overview of recommendation systems Collaborative filtering techniques Implementing recommendations with Spark MLlib Introduction to Graph Processing Overview of graph processing Use cases and applications of graph processing Graph representations and operations Introduction to Spark GraphX Overview of GraphX Creating and transforming graphs Graph algorithms in GraphX Big Data Innovation! Using GPT and Generative AI Technologies with Spark and Scala Overview of generative AI technologies Integrating GPT with Spark and Scala Practical applications and use cases Bonus Topics / Time Permitting Introduction to Spark NLP Overview of Spark NLP Preprocessing text data Text classification and sentiment analysis Putting It All Together Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.