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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.

Duration 3 Days 18 CPD hours This course is intended for Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform Overview This course teaches students the following skills: Derive insights from data using the analysis and visualization tools on Google Cloud Platform Interactively query datasets using Google BigQuery Load, clean, and transform data at scale Visualize data using Google Data Studio and other third-party platforms Distinguish between exploratory and explanatory analytics and when to use each approach Explore new datasets and uncover hidden insights quickly and effectively Optimizing data models and queries for price and performance Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL. Introduction to Data on the Google Cloud Platform Highlight Analytics Challenges Faced by Data Analysts Compare Big Data On-Premises vs on the Cloud Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud Navigate Google Cloud Platform Project Basics Lab: Getting started with Google Cloud Platform Big Data Tools Overview Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools Demo: Analyze 10 Billion Records with Google BigQuery Explore 9 Fundamental Google BigQuery Features Compare GCP Tools for Analysts, Data Scientists, and Data Engineers Lab: Exploring Datasets with Google BigQuery Exploring your Data with SQL Compare Common Data Exploration Techniques Learn How to Code High Quality Standard SQL Explore Google BigQuery Public Datasets Visualization Preview: Google Data Studio Lab: Troubleshoot Common SQL Errors Google BigQuery Pricing Walkthrough of a BigQuery Job Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs Optimize Queries for Cost Lab: Calculate Google BigQuery Pricing Cleaning and Transforming your Data Examine the 5 Principles of Dataset Integrity Characterize Dataset Shape and Skew Clean and Transform Data using SQL Clean and Transform Data using a new UI: Introducing Cloud Dataprep Lab: Explore and Shape Data with Cloud Dataprep Storing and Exporting Data Compare Permanent vs Temporary Tables Save and Export Query Results Performance Preview: Query Cache Lab: Creating new Permanent Tables Ingesting New Datasets into Google BigQuery Query from External Data Sources Avoid Data Ingesting Pitfalls Ingest New Data into Permanent Tables Discuss Streaming Inserts Lab: Ingesting and Querying New Datasets Data Visualization Overview of Data Visualization Principles Exploratory vs Explanatory Analysis Approaches Demo: Google Data Studio UI Connect Google Data Studio to Google BigQuery Lab: Exploring a Dataset in Google Data Studio Joining and Merging Datasets Merge Historical Data Tables with UNION Introduce Table Wildcards for Easy Merges Review Data Schemas: Linking Data Across Multiple Tables Walkthrough JOIN Examples and Pitfalls Lab: Join and Union Data from Multiple Tables Advanced Functions and Clauses Review SQL Case Statements Introduce Analytical Window Functions Safeguard Data with One-Way Field Encryption Discuss Effective Sub-query and CTE design Compare SQL and Javascript UDFs Lab: Deriving Insights with Advanced SQL Functions Schema Design and Nested Data Structures Compare Google BigQuery vs Traditional RDBMS Data Architecture Normalization vs Denormalization: Performance Tradeoffs Schema Review: The Good, The Bad, and The Ugly Arrays and Nested Data in Google BigQuery Lab: Querying Nested and Repeated Data More Visualization with Google Data Studio Create Case Statements and Calculated Fields Avoid Performance Pitfalls with Cache considerations Share Dashboards and Discuss Data Access considerations Optimizing for Performance Avoid Google BigQuery Performance Pitfalls Prevent Hotspots in your Data Diagnose Performance Issues with the Query Explanation map Lab: Optimizing and Troubleshooting Query Performance Advanced Insights Introducing Cloud Datalab Cloud Datalab Notebooks and Cells Benefits of Cloud Datalab Data Access Compare IAM and BigQuery Dataset Roles Avoid Access Pitfalls Review Members, Roles, Organizations, Account Administration, and Service Accounts

Duration 4 Days 24 CPD hours This course is intended for This is an intermediate course for individuals responsible for developing and implementing effective storage management techniques. Overview Establish a DFSMS configuration to automatically enforce your installation's storage management policies Convert service level requirements into appropriate parameters for data class, storage class, management class, and storage groups Create and test Automatic Class Selection (ACS) routines Convert volumes and move data to system-managed volumes with DFSMS Data Set Services (DFSMSdss) Specify appropriate management class and storage group parameters for DFSMS Hierarchical Storage Management (DFSMShsm) processing of system-managed data sets Plan to maintain your DFSMS environment using Naviquest Establish procedures to control, manage, and recover the storage management subsystem with ISMF and operator commands Develop a DFSMS implementation plan In this course you will learn how to plan and implement DFSMS and learn how to manage temporary and permanent data sets with an emphasis on disk storage. Course introduction and DFSMS overview Specify the storage administration functions that can be automatically performed by the system Identify the types of data set services that need to be established by negotiating service level agreements Correlate data set service requirements to the SMS configuration components: data class, storage class, management class, storage group, and automatic class selection routines Activating SMS Identify the functions eligible for exploitation with the installation of DFSMS Data Facility Product (DFSMSdfp) and the activation of SMS Create SMS control data sets Code SYS1.PARMLIB operands necessary to bring up SMS Create a minimal configuration Activate a configuration Writing ACS routines Identify the purpose of the ACS routines Develop an understanding of the statements Differentiate between literals and masks Describe the read variables available in the ACS routines Managing temporary data sets Create/alter storage classes and storage groups Identify steps to install and use the starter set Write ACS routines to handle temporary data sets Activate a system to manage temporary data sets Code commands to change volume/group SMS status Issue operator commands to display current status Exploiting DFSMS Describe the purpose of the data class Identify the features that the data class can exploit Create data sets using the space parameter Define Virtual Storage Access Method (VSAM) and volume attributes for data class Identify special data sets and their exploitation through the data class Managing permanent data sets Create/alter data classes, storage classes, management classes, and storage groups Translate current (DFSMShsm) service level agreements to management class parameters Identify alternatives and concerns for standard naming conventions Establish the controls for automatic backup of data sets Establish the controls for automatic volume dump Write ACS routines to manage permanent data Create a configuration that manages permanent data sets Create a new managed data set Identify function of storage class exit provided by Custom-Built Installation Process Offering (CBIPO) and resulting System Management Facility (SMF) records Using Naviquest Create test cases using Naviquest Perform storage administration tasks in batch Create online DFSMS reports Create model commands using Naviquest Use the COPYFILT macro Device preparation and data movement Initialize volumes as system-managed Move data into/out from system-managed control Convert volumes to/from system-managed Move data to utilize new hardware capabilities Controlling DFSMS Code commands to change SMS volume/group status Issue commands to save configurations and use alternate Active Control Data Set (ACDS) Issue command to use alternate Communication Data Set (COMMDS) Issue VARY SMS commands Communicate with the security administrator about storage management requirements Additional considerations Establish a plan for implementing SMS Locate sources of implementation planning checklists Identify the tools available to document the current system Identify multiple site considerations for recovery and exploitation Additional course details: Nexus Humans SS84 IBM DFSMS Implementation 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 SS84 IBM DFSMS Implementation 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 4 Days 24 CPD hours This course is intended for The primary audience for this course is as follows: Network Administrators Administrators interested in Automation Individuals interested in devops, specifically for networking Overview This course teaches students to blend Python skillsets with Ansible through the lens of automating networks. Automation techniques for the most popular vendor (incl. Cisco, Juniper, Arista) will be subjects of study, however, students may request examples from vendors within their own environments. Topics begin with a focus on automating networks with Python; this skill set is then folded into a broadening understanding of automating with Ansible. Students will have programmatic experience automating enterprise class networks by the conclusion of this course (includes writing custom Ansible modules with Python). Class is a combination of lecture, demonstration, and hands-on labs. Students are invited to share their own relevant Python and Ansible scripts with the instructor to ensure class subjects are as relevant as possible. All notes and scripts will be made available to students by the end of each day via a cloud-share or email. Lab time will be given reinforce that day's topics and demonstrations. No two networks are the same! Learn to automate your network with a Python and Ansible skillset. Course can be taught across all major (and most minor) network vendors. Course demonstrations can be adapted to best-fit the customer?s network to ensure all lessons have maximum relevance. Day 1 ? Critical Python Catchup & Review Overview of Python and Ansible Python white space rules & best practices Printing and more Printing Date types and Variables Packing and Unpacking Variables f Strings Conditional expressions Relational and Boolean operators Lists, Tuples, Dictionaries Indexing and slicing Built-in functions Iterating with Loops (for and while) Working with files Software Control Management (SCM) (Git, Github, Bitbucket, Cloudshare, etc.) Using Python to access REST interfaces Working with JSON Python, Ansible and Paramiko Using Paramiko to SSH with keys and passwords RESTful API review API keys Paramiko Review Using Paramiko to SFTP with keys and passwords Day 02 ? Python and Network Automation Introduction to Netmiko (automating routers and switches) Using Netmiko to send commands to / from network devices Working with YAML Converting JSON to YAML with Python Ansible keywords YAML and JSON for data exchange Ansible and YAML Ansible Playbook components Tying together Python and Ansible ? Using Python within Ansible Ansible Network Modules What is new in Ansible (most current updates / release notes) Network Agnostic modules Writing network playbooks Reviewing the construction of network playbooks Writing Ansible playbooks that respond to network failures Day 03 ? Blending Python and Ansible Skillsets Review how to use Python within Ansible Calling Python scripts with Ansible Jinja2 Templating Engine for Python (and Ansible) Using Templates in Ansible playbooks Jinja2 filters, looping, and other useful tricks for automating with Ansible Playbook tagging for selective runs When to use Python and when to use Ansible ?Big Picture? options for using Python & Ansible within your Network Ansible Roles Day 04 ? Customizing Ansible with Python Review ? Running Scripts with Ansible Prompting for Ansible user input Ansible Galaxy & Getting at Roles Writing a custom Ansible Module with Python Ansible ?Engine? vs Ansible ?Tower? ? marketing hype, capabilities, costs, etc. Case Study: Automate your Enterprise Network When to use Python and when to use Ansible Writing your own Ansible modules in Python ?Big Picture? options for using Python & Ansible within your Network Overview ? NETCONF / YANG and what they mean for Python and Ansible Molecule ? Testing your roles Additional course details: Nexus Humans Network Automation with Python and Ansible 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 Network Automation with Python and Ansible 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.

Dive into the intriguing world of forensic psychology with our comprehensive course. Explore the intersection of psychology and law, learning about criminal behavior, psychological profiling, and courtroom testimony. Gain valuable insights into the criminal justice system and forensic assessment techniques. Enroll now and embark on a journey into the fascinating realm of forensic psychology.

Learning Objectives Introduction , Interviewing Pitfalls , Before the Interview , During the Interview , After the Interview , Conclusion   Pre-Requisites There are no prerequisites for this course.   Description One of the most important decisions a company can make is hiring new employees. Good hiring decisions can make or break teams and can have a direct impact on a company's bottom line. Additionally, increasing diversity in hiring is about more than simple fair hiring practices. Research shows diverse teams make faster decisions and are more innovative. This class is designed to assist managers, supervisors, and HR staff in improving interviewing skills. Course Introduction Introduction 00:02:00 Section 01 Lesson 01: What is Unconscious Bias 00:05:00 Lesson 02: Overcoming Unconscious Bias 00:03:00 Section 02 Lesson 01: Creating the Job Description 00:03:00 Lesson 02: Planning the Questions 00:03:00 Lesson 03: Building a Scorecard 00:02:00 Lesson 04: Preparing for the Interview 00:02:00 Section 03 Lesson 01: Setting Candidates at Ease 00:01:00 Lesson 02: Conducting the Interview 00:03:00 Lesson 03: Selling the Job 00:02:00 Section 04 Lesson 01: Making the Big Decision 00:02:00 Course Recap Recap 00:01:00

Embark on a rewarding career path with our Personal Trainer Course. Gain the knowledge and skills to become a certified fitness professional. Learn about anatomy, exercise physiology, nutrition, and coaching techniques. Whether you're passionate about fitness or seeking to help others achieve their health goals, this course provides comprehensive training to excel as a personal trainer.

Unlock the secrets of number base conversion with our comprehensive course. Learn how to seamlessly transition between decimal, binary, octal, and hexadecimal systems. Master essential techniques and gain practical skills for solving complex mathematical problems with ease. Enroll now to expand your understanding of number bases and excel in various fields, from computer science to engineering.

So, you've recently passed your graduation and are looking for a job. Hundreds of others are doing the same and may be that the position you are applying for already has over 20 applicants. All of them have the same qualification and experience. They also read the same sample questions and prepare similarly for the job interview. So, how will you distinguish yourself from the rest? How can you ensure that you get noticed by the interviewers, and they pick you from the crowd? This course mainly aims at giving you an edge over the usual practice for the interviews. You will uncover the tips and tricks of the interviews that will make you more confident and helps you to handle all sorts of questions. You will learn to do brainstorming and list down all kind of questions- common, uncommon, and weird that could be asked. You will master the skills you need to excel at an interview. Course Highlights Interview Tips & Tricks is an award winning and the best selling course that has been given the CPD Certification & IAO accreditation. It is the most suitable course anyone looking to work in this or relevant sector. It is considered one of the perfect courses in the UK that can help students/learners to get familiar with the topic and gain necessary skills to perform well in this field. We have packed Interview Tips & Tricks into several modules for teaching you everything you need to become successful in this profession. To provide you ease of access, this course is designed for both part-time and full-time students. You can become accredited in just 20/30 hours and it is also possible to study at your own pace. We have experienced tutors who will help you throughout the comprehensive syllabus of this course and answer all your queries through email. For further clarification, you will be able to recognize your qualification by checking the validity from our dedicated website. Why You Should Choose Interview Tips & Tricks Lifetime access to the course No hidden fees or exam charges CPD Accredited certification on successful completion Full Tutor support on weekdays (Monday - Friday) Efficient exam system, assessment and instant results Download Printable PDF certificate immediately after completion Obtain the original print copy of your certificate, dispatch the next working day for as little as £9. Improve your chance of gaining professional skills and better earning potential. Who is this Course for? Interview Tips & Tricks is CPD certified and IAO accredited. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic backgrounds. Requirements Our Interview Tips & Tricks is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path You will be ready to enter the relevant job market after completing this course. You will be able to gain necessary knowledge and skills required to succeed in this sector. All our Diplomas' are CPD and IAO accredited so you will be able to stand out in the crowd by adding our qualifications to your CV and Resume. Importance of Knowing The Tips And Tricks for Interviews 00:15:00 The Different Types of Interviews 01:00:00 Skill Building to Crack Interviews 00:15:00 Tools and Miscellaneous You Need To Have 00:15:00 The Perfect 'Resume' - Significance and Importance 00:30:00 Preparing Properly for an Interview 00:30:00 What Role Does Appearance Play? 00:30:00 Tips To Gear Up - Pre-Interview 00:30:00 Modern Tips By Interview Experts 00:30:00 Mock Exam Mock Exam- Interview Tips & Tricks 00:20:00 Final Exam Final Exam- Interview Tips & Tricks 00:20:00

Master essential mathematical concepts in Number Sense, Algebra, and Analytic Geometry with our Grade 9 Maths Course. Explore foundational principles, problem-solving techniques, and real-world applications to build a solid mathematical foundation. Whether you're a student preparing for exams or seeking to strengthen your math skills, this course provides comprehensive instruction and practice to help you succeed in Grade 9 and beyond.