34 Educators providing Harvest courses delivered Live Online

Platelet-rich Plasma (PRP) treatments Nationally Recognised Qualification No previous experience or qualifications needed Open College Network Accreditation Level 4 (as required for minimally invasive procedures) Covers standards set by HEE Employed (salon) or Self-Employed opportunities Basic understanding of English language required OPEN TO ALL APPLICANTS

This day will introduce you to the basic techniques and skills involved in doing graphic facilitation. Learn how to use a BIG piece of paper and a handful of pens to create a memorable summary of your training day, team meeting or your work with young people and families. Learn how to harvest the essence of an event in a visual representation. This is a ‘hands on’ interactive day built around demonstrations of graphic facilitation, coaching and the chance to try things out. Ideal for teams who can then go on together to practice, practice, practice. Learning Objectives To introduce you to the basic skills of graphic facilitation – no previous experience is needed To develop your capacity to ‘listen under the words’ and draw out the deeper messages To help you suspend your self-doubt – “I can’t draw!” and rediscover your capacity to create an effective visual representation of a meeting/training day/conversation etc Course Content The day will introduce you to the fundamentals of graphic facilitation and will include the following topics: Pens, Pastels and Paper – what you will need to get started The basic ‘grammar’ of graphic facilitation; the essential shapes, using colour, images, lettering, words, creating connection How to listen for the essence of what is being said and translate this into visual language A chance to do it live – with coaching

About this training Mature fields differ from green field developments in that major infrastructure is in place, static reservoir data has accumulated from development drilling and a growing volume of production and processing performance data has become available. Decisions therefore relate to incremental projects, which may be small in scope and are often economically marginal. A firm understanding of the technical fundamentals associated with reservoir, wells and surface facilities is therefore required to make quality decisions in this environment, supported by realistic uncertainty ranges, and consistent application of incremental project economics and risk analysis. Various strategies may be considered to manage the mature asset, from harvest to divest, and the selected incremental activities should support a clear chosen strategy. Training Objectives Upon completion of this course, participants will be able to: Characterize the overall challenges associated with mature field developments Evaluate critical insights from subsurface data and apply this to modelling options and recovery methods Assess associated well data, typical late life issues and drilling and completion options for mature developments Manage the role of risk and uncertainty when making mature field development planning decisions Prepare a strategy and implementation plan Target Audience The course is intended for individuals who play a part in evaluating, screening and maturing oil and gas field development opportunities. The following personnel will benefit from the knowledge shared in this course: Petroleum engineers Geoscientist Facilities engineers Commercial staffs Reservoir engineer Production engineer Drilling engineer Project manager Asset manager Field engineer Exploration manager Course Level Basic or Foundation Trainer Your expert course leader, boasts nearly four decades of experience in the upstream oil & gas industry. He began his career in the back in 1982, spending 13 years with Shell International across several global locations. During his tenure, he served primarily as a reservoir engineer, contributing to exploration prospect evaluation, field development planning, corporate business planning, and drilling operations. Throughout his career, he has executed a diverse range of reservoir engineering projects for multiple UK and international firms, and has successfully led several PE study teams. Furthermore, he has continuously provided reservoir engineering and commercial training to oil company staff on a national and international scale. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations

Duration 3 Days 18 CPD hours This course is intended for Individuals involved in IT development, IT operations or IT service management; Those whose role is touched by DevOps and continuous delivery, such as the following IT roles: DevOps engineers, Product owners Integration specialists, Operations managers, Incident & change managers, System administrators, Network administrators, Business managers, Automation architects, Enterprise architects, Testers Overview Know the emergence of DevOps Know the core concepts and principles of DevOps Know what DevOps means for you as professional and for your organization Know the essence of a DevOps culture Understand the key elements of a DevOps culture Know the important aspects when creating a DevOps culture Know the Operational models of DevOps Understand the need for autonomous teams Understand the impact of DevOps on Architecture with respect to deployment Understand governance within DevOps teams Understand Agile, Scrum and Kanban and how these practices relate to one another Understand how ITSM processes relate to practices in a DevOps culture Understand how lean is used to optimise processes Know how to provide a Value Stream Map for a given process Understand the way to harvest new and innovative ideas Know the impact of automation on Software Delivery processes Understand the benefits and core principles of Continuous Delivery Describe the key cloud principles for DevOps organisations Know the relevance of monitoring and logging DevOps This course is designed to provide the core education necessary to build your DevOps vocabulary and to understand its principles and practices. With the help of key DevOps concepts and terminology, real-life case studies, examples and interactive group discussions and extensive exercises in each module you will acquire a fundamental understanding of DevOps. Introduction Let?s Get to Know Each Other Overview Course Objectives Mapping of the Competence Model with the Course Modules Course Agenda Type of Activities Exam Course Book Technical Glossary Group Activity Module Summary DevOps Introduction Module Objectives Module Topics Emergence of DevOps Core Concepts of DevOps DevOps Agile Skills Association (DASA) Module Summary Module End Questions Culture Module Objectives Module Topics Essence of a DevOps Culture Key Elements of DevOps Implementation of a DevOps Culture Module Summary Module End Questions Organization Module Objectives Module Topics Organizational Model Autonomous Teams Architecting for DevOps Governance Module Summary Module End Questions Processes Module Objectives Module Topics Process Basics DevOps in Relation to ITSM Agile and Scrum 12 Principles of the Agile Manifesto Optimizing Processes Using Lean Business Value Optimization and Business Analysis Using Story Mapping Module Summary Module End Questions Automation Module Objectives 6A Automation Concepts Automation for Delivery of Software Continuous Delivery Core Concepts Continuous Delivery Automation Concepts Continuous Delivery Automation Focus Topics 6B Data Center Automation Emergence of Cloud Technology and Principles Cloud Services Concepts in a DevOps Organization Automated Provisioning Concepts Platform Product Characteristics and Application Maturity Module Summary Module End Questions Measure and Improvement Module Objectives Module Topics Importance of Measurement Choosing the Right Metrics Monitoring and Logging Module Summary Module End Questions

Duration 4 Days 24 CPD hours This course is intended for Security engineers Security administrators Security architects Operations engineers Network engineers Network administrators Network or security technicians Network managers System designers Cisco integrators and partners Overview After taking this course, you should be able to: Describe and administer the Cisco Email Security Appliance (ESA) Control sender and recipient domains Control spam with Talos SenderBase and anti-spam Use anti-virus and outbreak filters Use mail policies Use content filters Use message filters to enforce email policies Prevent data loss Perform LDAP queries Authenticate Simple Mail Transfer Protocol (SMTP) sessions Authenticate email Encrypt email Use system quarantines and delivery methods Perform centralized management using clusters Test and troubleshoot This course shows you how to deploy and use Cisco© Email Security Appliance to establish protection for your email systems against phishing, business email compromise, and ransomware, and to help streamline email security policy management. This hands-on course provides you with the knowledge and skills to implement, troubleshoot, and administer Cisco Email Security Appliance, including key capabilities such as advanced malware protection, spam blocking, anti-virus protection, outbreak filtering, encryption, quarantines, and data loss prevention. This course helps you prepare to take the exam, Securing Email with Cisco Email Security Appliance (300-720 SESA). Describing the Cisco Email Security Appliance Cisco Email Security Appliance Overview Technology Use Case Cisco Email Security Appliance Data Sheet SMTP Overview Email Pipeline Overview Installation Scenarios Initial Cisco Email Security Appliance Configuration Centralizing Services on a Cisco Administering the Cisco Email Security Appliance Distributing Administrative Tasks System Administration Managing and Monitoring Using the Command Line Interface (CLI) Other Tasks in the GUI Advanced Network Configuration Using Email Security Monitor Tracking Messages Logging Controlling Sender and Recipient Domains Public and Private Listeners Configuring the Gateway to Receive Email Host Access Table Overview Recipient Access Table Overview Configuring Routing and Delivery Features Controlling Spam with Talos SenderBase and Anti-Spam SenderBase Overview Anti-Spam Managing Graymail Protecting Against Malicious or Undesirable URLs File Reputation Filtering and File Analysis Bounce Verification Using Anti-Virus and Outbreak Filters Anti-Virus Scanning Overview Sophos Anti-Virus Filtering McAfee Anti-Virus Filtering Configuring the Appliance to Scan for Viruses Outbreak Filters How the Outbreak Filters Feature Works Managing Outbreak Filters Using Mail Policies Email Security Manager Overview Mail Policies Overview Handling Incoming and Outgoing Messages Differently Matching Users to a Mail Policy Message Splintering Configuring Mail Policies Using Content Filters Content Filters Overview Content Filter Conditions Content Filter Actions Filter Messages Based on Content Text Resources Overview Using and Testing the Content Dictionaries Filter Rules Understanding Text Resources Text Resource Management Using Text Resources Using Message Filters to Enforce Email Policies Message Filters Overview Components of a Message Filter Message Filter Processing Message Filter Rules Message Filter Actions Attachment Scanning Examples of Attachment Scanning Message Filters Using the CLI to Manage Message Filters Message Filter Examples Configuring Scan Behavior Preventing Data Loss Overview of the Data Loss Prevention (DLP) Scanning Process Setting Up Data Loss Prevention Policies for Data Loss Prevention Message Actions Updating the DLP Engine and Content Matching Classifiers Using LDAP Overview of LDAP Working with LDAP Using LDAP Queries Authenticating End-Users of the Spam Quarantine Configuring External LDAP Authentication for Users Testing Servers and Queries Using LDAP for Directory Harvest Attack Prevention Spam Quarantine Alias Consolidation Queries Validating Recipients Using an SMTP Server SMTP Session Authentication Configuring AsyncOS for SMTP Authentication Authenticating SMTP Sessions Using Client Certificates Checking the Validity of a Client Certificate Authenticating User Using LDAP Directory Authenticating SMTP Connection Over Transport Layer Security (TLS) Using a Client Certificate Establishing a TLS Connection from the Appliance Updating a List of Revoked Certificates Email Authentication Email Authentication Overview Configuring DomainKeys and DomainKeys Identified Mail (DKIM) Signing Verifying Incoming Messages Using DKIM Overview of Sender Policy Framework (SPF) and SIDF Veri?cation Domain-based Message Authentication Reporting and Conformance (DMARC) Verification Forged Email Detection Email Encryption Overview of Cisco Email Encryption Encrypting Messages Determining Which Messages to Encrypt Inserting Encryption Headers into Messages Encrypting Communication with Other Message Transfer Agents (MTAs) Working with Certificates Managing Lists of Certificate Authorities Enabling TLS on a Listener?s Host Access Table (HAT) Enabling TLS and Certi?cate Verification on Delivery Secure/Multipurpose Internet Mail Extensions (S/MIME) Security Services Using System Quarantines and Delivery Methods Describing Quarantines Spam Quarantine Setting Up the Centralized Spam Quarantine Using Safelists and Blocklists to Control Email Delivery Based on Sender Configuring Spam Management Features for End Users Managing Messages in the Spam Quarantine Policy, Virus, and Outbreak Quarantines Managing Policy, Virus, and Outbreak Quarantines Working with Messages in Policy, Virus, or Outbreak Quarantines Delivery Methods Centralized Management Using Clusters Overview of Centralized Management Using Clusters Cluster Organization Creating and Joining a Cluster Managing Clusters Cluster Communication Loading a Configuration in Clustered Appliances Best Practices Testing and Troubleshooting Debugging Mail Flow Using Test Messages: Trace Using the Listener to Test the Appliance Troubleshooting the Network Troubleshooting the Listener Troubleshooting Email Delivery Troubleshooting Performance Web Interface Appearance and Rendering Issues Responding to Alerts Troubleshooting Hardware Issues Working with Technical Support References Model Specifications for Large Enterprises Model Specifications for Midsize Enterprises and Small-to-Midsize Enterprises or Branch O?ces Cisco Email Security Appliance Model Specifications for Virtual Appliances

THIS COURSE PACKAGE INCLUDES: 1: PERIPHERAL I.V. CANNULATION - IV THERAPIES COURSE (GPT008) 2: VACCINATION / INJECTION COURSE (GPT601) Learn how to administer injectables and intravenous therapies ... FAST-TRACK YOUR AESTHETICS TRAINING WITH OUR COMPLETE TRAINING PACKAGE 20% Multi-Course Discount Cover all stages from Level 1 through to Level 4 (FDSc) Cover your theory training online Complete your advanced practical training in 1 day Practical training in Classroom or Virtual Classroom Comprehensive Practise@Home training kits for VC Awards 2 accredited qualifications Dual Accreditations for all courses Covers all steps required to safely perform injectables Covers all steps required to safely perform IV therapies Practise IV on artificial arm with fake blood Practise injection techniques on realistic injection pads Learn beginner to advanced skills and techniques Basic understanding of English language required OPEN TO ALL APPLICANTS

EXPERT – MASTERCLASS 8 CPD POINTS 1 DAY INTENSIVE COURSE  ONLINE or IN-CLINIC NOTE! After booking we will contact you for scheduling the exact course date! Courses dates are subject to change due to mentors availability. We will inform you via email if a date becomes available! DERMAGRAFT AND ENRICHED NANO-MICROFAT TRANSFER FOR FACE, NECK & HANDS – VOLUMIZATION & REJUVINATION WHAT IS MICROFAT AND NANOFAT GRAFTING FOR FACE AND NECK LIFT? Microfat and enriched nanofat graft transfer (also known as autologous fat transfer or lipoinjection), to the face and the neck is a minimally invasive, short-lasting procedure with rapid recovery, and can be done under local anaesthesia. Following completion of the procedure, the patient can return to the normal daily life activities. But firstly, we need to clearly explain what the terms microfat and nanofat grafts mean…. Microfat is defined a small-diameter fat particle and is used to improve the appearance of wrinkles, grooves and the lack of volume and sagginess of the skin of the face and neck, in response to the aging process. Similarly, nanofat, is referred to as the smallest diameter fat particle. The main advantage of the nanofat is that it contains cells that have the ability to differentiate in any type of body cell. Stem cells – as they are called- play a very important role in the process of rejuvenation, as they can differentiate into cells called fibroblasts which in turn produce collagen thus making the skin firmer and more youthful in appearance. The Course can be divided into two stages: 1. In the first stage, fat cells will be obtained from one or more parts of the body and are then purified and injected into the face and the neck. The doctor will identify an area in your body where the fat will be obtained from. This area is usually the flanks, but fat can also be obtained from other areas such as the abdomen, and the outer and inner thighs. You will be given enough local anaesthesia to numb the area where the fat will be harvested from. Then, a small-diameter cannula called microcannula connected to a special vacuum syringe will be gently introduced under the skin to obtain the fat. During this process, you should not feel any pain, the local anaesthetic will have made you numb. After the fat is harvested, it will contain a mixture of fat cells, blood, water, and local anaesthetic. Therefore, this fat will not be pure. This mixture of fat, blood, water and local anaesthetic will then become filtered into a special filtering and processing device whereby all the blood, water and local anaesthetic are being washed out, so that pure fat remains. This fat is then further processed by passing it through special filters whereby it becomes a smaller-sized fat particle known as microfat and nanofat graft. You need to be medically qualified as a doctor, dentist, nurse, pharmacist or paramedic with full governing body registration and have completed a Foundation Filler Course and to have administered a number of cases. Additional information ATTENDANCE ONLINE (theory), IN-CLINIC (Practice) COURSE LEVEL EXPERT | Masterclass Course

Innovation Project Management: Virtual In-House Training Companies need growth for survival. Companies cannot grow simply through cost reduction and reengineering efforts. This program describes the relationship that needs to be established between innovation, business strategy, and project management to turn a creative idea into a reality. We will explore the importance of identifying the components of an innovative culture, existing differences, challenges, and the new set of skills needed in innovation project management. Companies need growth for survival. Companies cannot grow simply through cost reduction and reengineering efforts. Innovation is needed and someone must manage these innovation projects. Over the past two decades, there has been a great deal of literature published on innovation and innovation management. Converting a creative idea into reality requires projects and some form of project management. Unfortunately, innovation projects, which are viewed as strategic projects, may not be able to be managed using the traditional project management philosophy we teach in our project management courses. There are different skill sets needed, different tools, and different life-cycle phases. Innovation varies from industry to industry and even companies within the same industry cannot come to an agreement on how innovation project management should work. This program describes the relationship that needs to be established between innovation, business strategy, and project management to turn a creative idea into a reality. We will explore the importance of identifying the components of an innovative culture, existing differences, challenges, and the new set of skills needed in innovation project management. What you Will Learn Explain the links needed to bridge innovation, project management, and business strategy Describe the different types of innovation and the form of project management each require Identify the differences between traditional and innovation project management, especially regarding governance, human resources management challenges, components of an innovative culture and competencies needed by innovation project managers Establish business value and the importance of new metrics for measuring and reporting business value Relate innovation to business models and the skills needed to contribute in the business model development Recognize the roadblocks affecting innovation project management and their cause to determine what actions can be taken Determine the success and failure criteria of an innovation project Foundation Concepts Understanding innovation Role of innovation in a company Differences between traditional (operational) and strategic projects Innovation management Differences between innovation and R&D Differing views of innovation Why innovation often struggles Linking Innovation Project Management to Business Strategy The business side of innovation project management The need for innovation targeting Getting close to the customers and their needs The need for line-of-sight to the strategic objectives The innovation enterprise environmental factors Tools for linking Internal Versus External (Co-creation) Innovation Open versus closed innovation Open innovation versus crowdsourcing Benefits of internal innovation Benefits of co-creation (external) innovation Selecting co-creation partners The focus of co-creation The issues with intellectual property Understanding co-creation values Understanding the importance of value-in-use Classification of Innovations and Innovation Projects Types of projects Types of innovations Competency-enhancing versus competency-destroying innovations Types of innovation novelty Public Sector of Innovation Comparing public and private sector project management Types of public service innovations Reasons for some public sector innovation failures An Introduction to Innovation Project Management Why traditional project management may not work The need for a knowledge management system Differences between traditional and innovation project management Issues with the 'one-size-fits-all' methodology Using end-to-end innovation project management Technology readiness levels (TRLs) Integrating Kanban principles into innovation project management Innovation and the Human Resources Management Challenge Obtaining resources Need for a talent pipeline Need for effective resource management practices Prioritizing resource utilization Using organizational slack Corporate Innovation Governance Types of innovation governance Business Impact Analysis (BIA) Innovation Project Portfolio Management Office (IPPMO) Using nondisclosure agreements, secrecy agreements, confidentiality agreements, and patents Adverse effects of governance decisions Innovation Cultures Characteristics of a culture for innovation Types of cultures Selecting the right people Linking innovation to rewards Impact of the organizational reward system Innovation Competencies Types of innovation leadership The need for active listening Design thinking Dealing with ambiguity, uncertainty, risks, crises, and human factors Value-Based Innovation Project Management Metrics Importance of innovation project management metrics Understanding value-driven project management Differences between benefits and value - and when to measure Traditional versus the investment life cycle Benefits harvesting Benefits and value sustainment Resistance to change Tangible and intangible innovation project management metrics Business Model Innovation Business model characteristics Impact of disruptive innovation Innovation Roadblocks Roadblocks and challenges facing project managers Ways to overcome the roadblocks Defining Innovation Success and Failure Categories for innovation success and failure Need for suitability and exit criteria Reasons for innovation project failure Predictions on the Future of Innovation Project Management The Six Pillars of changing times Some uses for the new value and benefits metrics

Duration 1 Days 6 CPD hours This course is intended for It is essential information for beginning IT Asset Managers and other IT professionals involved in asset management, resource budgeting, finance, software licensing, contract management and strategic planning. Overview During this course, students learn best practices in Software Asset Management Reducing Risk Increasing Accountability Uncovering Savings Gaining Control of the IT Environment The IAITAM Certified Software Asset Manager (CSAM) Course is a foundational education program that ensures students are able to manage software assets. Students also learn about the ever-changing variables throughout our industry. From software piracy and compliance issues to legislation and organizational challenges, it is necessary to evaluate both the internal and external influences that bring about change in how organizations manage their IT assets. A successful Software Asset Manager must look at the overall goals of the organization and determine where Software Asset Management will be a strategic influence in achieving those goals. This course also includes the exam for CSAM certification. Course Outline The Scope of Software Strategic License Management Software Harvesting License Documentation The Right to Audit Proactive vs. Reactive SAM Developing Goals Savings Opportunities ITAM Compliance Audit Letter Examples of License Data Documentation Compliance Enforcement Understanding the EULA Due Diligence for Compliance The Art of Negotiation Ts & Cs Advice ITAM Automation Selecting a Discovery Tool ITAM Repository Hardware & Organizational Impacts Additional course details: Nexus Humans Certified Software Asset Manager (CSAM) 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 Certified Software Asset Manager (CSAM) 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 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm