This course will help you prepare for the AI-900 Exam: Microsoft Azure AI Fundamentals. We will cover the complete exam syllabus as updated in April 2021 with sample questions.
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
Description: If you have already covered the basics of Python in programming, you know it already that it is an awesome language to continue learning. Hence this Python 3 intermediate course. You will be amazed how much you can do in Python. Python is a powerful high-level, object-oriented programming language. It is a great object oriented programming language which is good to have under your belt. You can turn your idea into a prototype or create games or get started with data Science, python can help you in everything to get started. It has simple easy-to-use syntax, making it the perfect language for someone trying to make a great career in programming. Assessment: At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After you have successfully passed the test, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. PDF certificate's turnaround time is 24 hours and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognised accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Who is this Course for? Python 3 Intermediate is certified by CPD Qualifications Standards and CiQ. 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 background. Requirements Our Python 3 Intermediate 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 After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Python 3 Intermediate Iterators and Generators FREE 00:16:00 Regular Expressions 00:19:00 Introspection and Lambda Functions 00:27:00 Metaclasses and Decorators 00:24:00 Modules and Packages 00:25:00 Working with APIs 00:15:00 Metaprogramming Primer 00:19:00 Decorators and Monkey Patching 00:21:00 XML and JSON Structure 00:10:00 Generating XML and JSON 00:17:00 Parsing XML and JSON 00:19:00 Implementing Algorithms 00:19:00 Mock Exam Mock Exam- Python 3 Intermediate 00:20:00 Final Exam Final Exam- Python 3 Intermediate 00:20:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00
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The Software Developer & Software Testing course is self-paced and can be taken from the comfort of your home, office, or on the go! With our Student ID card you will get discounts on things like music, food, travel and clothes etc. Software Developer Skills Proficiency in programming languages like Python, Java, C++, JavaScript, or Ruby. Problem-solving skills for analyzing and resolving complex issues. Knowledge of algorithms and data structures for optimizing code efficiency. Ability to debug and fix errors in code effectively. Familiarity with version control tools like Git. Understanding of web development technologies including HTML, CSS, and JavaScript frameworks. Competence in database management systems such as SQL or NoSQL. Experience with software testing frameworks and methodologies. Proficiency in object-oriented design principles. Knowledge of continuous integration/continuous deployment (CI/CD) pipelines. Familiarity with Agile methodologies like Scrum or Kanban. 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Duration 5 Days 30 CPD hours This course is intended for This course is targeted towards the information technology (IT) professional that has a minimum 1 year IT Security and Networking experience. This course would be ideal for Information System Owners, Security Officers, Ethical Hackers, Information Owners, Penetration Testers, System Owner and Managers as well as Cyber Security Engineers. Overview Upon completion, the Certified Professional Ethical Hacker candidate will be able to competently take the CPEH exam. The CPEH certification training enables students to understand the importance of vulnerability assessments and how to implement counter response along with preventative measures when it comes to a network hack. Security Fundamentals Overview The Growth of Environments and Security Our Motivation? The Goal: Protecting Information! CIA Triad in Detail Approach Security Holistically Security Definitions Definitions Relationships Method: Ping The TCP/IP Stack Which Services Use Which Ports? TCP 3-Way Handshake TCP Flags Malware Types of Malware Types of Malware Cont... Types of Viruses More Malware: Spyware Trojan Horses Back Doors DoS DDoS Packet Sniffers Passive Sniffing Active Sniffing Firewalls, IDS and IPS Firewall ? First Line of Defense IDS ? Second Line of Defense IPS ? Last Line of Defense? Firewalls Firewall Types: (1) Packet Filtering Firewall Types: (2) Proxy Firewalls Firewall Types ? Circuit-Level Proxy Firewall Type of Circuit- Level Proxy ? SOCKS Firewall Types ? Application-Layer Proxy Firewall Types: (3) Stateful Firewall Types: (4) Dynamic Packet-Filtering Firewall Types: (5) Kernel Proxies Firewall Placement Firewall Architecture Types ? Screened Host Multi- or Dual-Homed Screened Subnet Wi-Fi Network Types Wi-Fi Network Types Widely Deployed Standards Standards Comparison 802.11n - MIMO Overview of Database Server Review Access Controls Overview Role of Access Control Definitions More Definitions Categories of Access Controls Physical Controls Logical Controls ?Soft? Controls Security Roles Steps to Granting Access Access Criteria Physical Access Control Mechanisms Biometric System Types Synchronous Token Asynchronous Token Device Memory Cards Smart Card Cryptographic Keys Logical Access Controls OS Access Controls Linux Access Controls Accounts and Groups Password & Shadow File Formats Accounts and Groups Linux and UNIX Permissions Set UID Programs Trust Relationships Review Protocols Protocols Overview OSI ? Application Layer OSI ? Presentation Layer OSI ? Session Layer Transport Layer OSI ? Network Layer OSI ? Data Link OSI ? Physical Layer Protocols at Each OSI Model Layer TCP/IP Suite Port and Protocol Relationship Conceptual Use of Ports UDP versus TCP Protocols ? ARP Protocols ? ICMP Network Service ? DNS SSH Security Protocol SSH Protocols ? SNMP Protocols ? SMTP Packet Sniffers Example Packet Sniffers Review Cryptography Overview Introduction Encryption Cryptographic Definitions Encryption Algorithm Implementation Symmetric Encryption Symmetric Downfalls Symmetric Algorithms Crack Times Asymmetric Encryption Public Key Cryptography Advantages Asymmetric Algorithm Disadvantages Asymmetric Algorithm Examples Key Exchange Symmetric versus Asymmetric Using the Algorithm Types Together Instructor Demonstration Hashing Common Hash Algorithms Birthday Attack Example of a Birthday Attack Generic Hash Demo Instructor Demonstration Security Issues in Hashing Hash Collisions MD5 Collision Creates Rogue Certificate Authority Hybrid Encryption Digital Signatures SSL/TLS SSL Connection Setup SSL Hybrid Encryption SSH IPSec - Network Layer Protection IPSec IPSec Public Key Infrastructure Quantum Cryptography Attack Vectors Network Attacks More Attacks (Cryptanalysis) Review Why Vulnerability Assessments? Overview What is a Vulnerability Assessment? Vulnerability Assessment Benefits of a Vulnerability Assessment What are Vulnerabilities? Security Vulnerability Life Cycle Compliance and Project Scoping The Project Overview Statement Project Overview Statement Assessing Current Network Concerns Vulnerabilities in Networks More Concerns Network Vulnerability Assessment Methodology Network Vulnerability Assessment Methodology Phase I: Data Collection Phase II: Interviews, Information Reviews, and Hands-On Investigation Phase III: Analysis Analysis cont. Risk Management Why Is Risk Management Difficult? Risk Analysis Objectives Putting Together the Team and Components What Is the Value of an Asset? Examples of Some Vulnerabilities that Are Not Always Obvious Categorizing Risks Some Examples of Types of Losses Different Approaches to Analysis Who Uses What? Qualitative Analysis Steps Quantitative Analysis ALE Values Uses ALE Example ARO Values and Their Meaning ALE Calculation Can a Purely Quantitative Analysis Be Accomplished? Comparing Cost and Benefit Countermeasure Criteria Calculating Cost/Benefit Cost of a Countermeasure Can You Get Rid of All Risk? Management?s Response to Identified Risks Liability of Actions Policy Review (Top-Down) Methodology Definitions Policy Types Policies with Different Goals Industry Best Practice Standards Components that Support the Security Policy Policy Contents When Critiquing a Policy Technical (Bottom-Up) Methodology Review Vulnerability Tools of the Trade Vulnerability Scanners Nessus SAINT ? Sample Report Tool: Retina Qualys Guard http://www.qualys.com/products/overview/ Tool: LANguard Microsoft Baseline Analyzer MBSA Scan Report Dealing with Assessment Results Patch Management Options Review Output Analysis and Reports Overview Staying Abreast: Security Alerts Vulnerability Research Sites Nessus SAINT SAINT Reports GFI Languard GFI Reports MBSA MBSA Reports Review Reconnaissance, Enumeration & Scanning Reconnaissance Overview Step One in the Hacking ?Life-Cycle? What Information is Gathered by the Hacker? Passive vs. Active Reconnaissance Footprinting Defined Social Access Social Engineering Techniques Social Networking Sites People Search Engines Internet Archive: The WayBack Machine Footprinting Tools Overview Maltego GUI Johnny.Ihackstuff.com Google (cont.) Domain Name Registration WHOIS Output DNS Databases Using Nslookup Traceroute Operation Web Server Info Tool: Netcraft Introduction to Port Scanning Which Services use Which Ports? Port Scan Tips Port Scans Shou
Kickstart your journey into deep learning and gain a strong understanding of deep neural networks through practical exercises. Develop your intuition and learn the fundamentals of artificial neural networks, activation functions, and loss functions. Gain practical experience with Python and TensorFlow 2.x, and apply your skills to build powerful deep learning models.
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This Data Analysis with Data Science & Machine Learning Bundle Consists of the following Premium courses: Course 01: Introduction to Data Analysis Course 02: Data Analytics with Tableau Course 03: Complete Google Analytics Course Course 04: Python for Data Analysis Course 05: Quick Data Science Approach from Scratch Course 06: R Programming for Data Science Course 07: Learn MySQL from Scratch for Data Science and Analytics Course 08: Master JavaScript with Data Visualization Course 09: Excel Data Analysis Course 10: Statistics & Probability for Data Science & Machine Learning Course 11: Root Cause Analysis Course 12: Google Data Studio: Data Analytics Course 13: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query Course 14: Business Intelligence and Data Mining Masterclass Learning Outcomes: Develop a solid understanding of data analysis techniques. Learn how to collect, manage, and manipulate data effectively. Gain knowledge in the programming languages commonly used in data analysis, such as Python and R. Become proficient in data visualisation and presentation. Develop an understanding of machine learning algorithms and their application in data analysis. Learn how to use various data analysis software, including Tableau and Google Analytics. The Data Analysis with Data Science & Machine Learning bundle includes a variety of courses aimed at providing theoretical knowledge in the field of data analysis. The bundle covers a wide range of topics, starting with the basics of data analysis such as data cleaning, exploration, and visualisation. With courses such as Introduction to Data Analysis, Data Analytics with Tableau, Complete Google Analytics Course, Python for Data Analysis, Quick Data Science Approach from Scratch, R Programming for Data Science, Learn MySQL from Scratch for Data Science and Analytics, and Master JavaScript with Data Visualization, learners can get a comprehensive understanding of data analysis concepts. The course material is presented in a theoretical format to help learners gain a deep understanding of the topics. Learners can engage with the material at their own pace. The course content is presented in a way that is easy to understand, making it ideal for those who are new to the field of data analysis. Course Curriculum: Data Analysis with Data Science & Machine Learning Module 01: Introduction Module 02: Agenda and Principles of Process Management Module 03: The Voice of the Process Module 04: Working as One Team for Improvement Module 05: Exercise: The Voice of the Customer Module 06: Tools for Data Analysis Module 07: The Pareto Chart Module 08: The Histogram Module 09: The Run Chart Module 10: Exercise: Presenting Performance Data Module 11: Understanding Variation Module 12: The Control Chart Module 13: Control Chart Example Module 14: Control Chart Special Cases Module 15: Interpreting the Control Chart Module 16: Control Chart Exercise Module 17: Strategies to Deal with Variation Module 18: Using Data to Drive Improvement Module 19: A Structure for Performance Measurement Module 20: Data Analysis Exercise Module 21: Course Project Module 22: Test your Understanding CPD 140 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Professionals seeking to upskill and enhance their data analysis knowledge and abilities. Individuals interested in pursuing a career in data analysis, data science or machine learning. Business owners or entrepreneurs looking to gain insights into their data and make data-driven decisions. Students or recent graduates seeking to gain valuable experience and knowledge in data analysis. Anyone looking to expand their knowledge and understanding of data analysis and its useful applications. Requirements This Data Analysis with Data Science & Machine Learning course has been designed to be fully compatible with tablets and smartphones. Career path Data Analyst: £24k-£42k per annum. Business Intelligence Analyst: £25k-£60k per annum. Data Scientist: £27k-£65k per annum. Machine Learning Engineer: £28k-£80k per annum. Business Analyst: £24k-£52k per annum. Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - £10 You will get the Hard Copy certificate for the Data Analysis with Data Science & Machine Learning course absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.
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