30 Python courses

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Ansible training course description The course focusses on the use of ansible for network devices instead of its usual server use case. The course progresses from the basics of ansible and playbooks onto using network specific modules including NAPALM. The use Jinja2 templating with ansible is also studied. Hands on sessions with ansible configuring routers and switches follow all major sections. What will you learn Automate tasks with ansible. Write ansible playbooks. Configure network devices with ansible. Troubleshoot network devices with ansible. Use ansible network modules. Use jinja2 templates with ansible. Ansible training course details Who will benefit: Network engineers. Prerequisites: TCP/IP Foundation Duration 2 days Ansible training course contents What is ansible? The language, the engine, the framework. Uses of ansible, orchestration. Hands on Installing ansible, enabling SSH on network devices. Ansible architecture How ansible 'normally' works, Agentless, SSH, ansible and Python, modules, how ansible work on network devices, Configuration management, inventories, playbooks, modules, ansible.cfg. Hands on Getting started, running ad hoc commands. Playbooks ansible-playbook, users, YAML, plays, tasks, modules. ansible-vault. Hands on Running playbooks. More playbooks Handlers, variables, environmental variables, playbook variables, inventory variables, variable scope and precedence, accessing variables, facts, ansible vault. Conditionals, wait_for. Hands on Using variables and conditions in playbooks. Inventories /etc/ansible/hosts, inventory variables, static inventories, dynamic inventories. Hands on Inventories and variables. Ansible network modules Built in modules, custom modules, return values. ansible-doc -l. connection: local, Cisco modules, Juniper module, Hands on Using modules for your network devices. Ansible templatings The template module, the assemble module, jinja2 templates, for, if else. Hands on Configuring network devices from templates. Roles and includes Dynamic includes, Handler includes, playbook includes. Roles, role parts: handlers, files, templates, cross platform roles, ansible galaxy. Hands on includes example, building roles. Ansible and NAPALM Installation, napalm-ansible, NAPALM modules: napalm_diff-yang, napalm_get_facts, napalm_install_config, napalm_parse_yang, napalm_ping, napalm_translate_yang, napalm_validate. Hands on Using NAPALM modules in ansible.

This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.

Definitive Salt training course description Salt is a remote execution framework and configuration management system. This course covers Salt from the basics. After a quick first taste the course moves onto execution modules, salt states, minion and master data, jinja, Salt extensions and then topology and configuration options. Hands on sessions are used to reinforce the theory rather than teach specific manufacturer equipment. What will you learn Install and use Salt. Describe the architecture of Salt. Manage configurations with Salt. Extend Salt. Definitive Salt training course details Who will benefit: Anyone working with Salt. Prerequisites: Linux fundamentals. Duration 2 days Definitive Salt training course contents Introduction What is Salt? High- level architecture, Some quick examples, system management, configuration management, A brief history, Topology options, Extending Salt. Quick start: First taste of Salt Single-master setup, from packages, bootstrap scripts, Starting up, Basic commands, salt: the main workhorse, salt-key: key management, salt-call: execution on the minion, salt-run: co-ordination of jobs on the master, summary of commands, Key management, viewing keys, accepting keys, rejecting keys, key files, Minion targeting, minion ID, list (-L), glob, regular expressions (-E), grains (-G), compound (-C), targeting summary, Additional remote execution details, Conclusion. Execution modules: The functional foundation sys: information and documentation about modules, sys.doc basic documentation, sys.list_modules, sys.list_functions: simple listings, cmd: execute via shell, cmd.run: run any command, pkg: manage packages, virtual modules, pkg.lists_pkgs: list all installed packages, pkg.available version: see what version will be installed, pkg.install: install packages, user: manage users, user.add: add users, user.list_users, user info: get user info, saltutil: access various Salt utilities, Summary. Configuration management: Salt states Salt files overview, SLS example: adding a user, working with the multi-layered state system, Highstate and the top file, the top file, State ordering, require: depend on another state, watch: run based on other changes, odds and ends, Summary. Minion data / master data Grains are minion data, performing basic grain operations, setting grains, targeting with grains in the top file, Pillars are data from the master, querying pillar data, querying other sources with external pillars, Renderers give data options. Extending Salt: part I Introduction to Jinja, Jinja basics, Templating with Jinja, filtering by grains, Custom execution module, Custom state modules, Custom grains, External pillars, Summary. More on the matter Runners, manage minions, manage jobs, The orchestrate runner, The event system, The reactor system, Summary. Extending Salt: part II Python client API, reading configuration data on a master and minion, using the master client (localclient) API, Using the caller client API, Custom runners, writing a custom runner, using the runnerclient API, Summary. Topology and configuration options Master configuration, directories and files, logging, access control, files server options, Topology variations, masterless minions, peer systems, syndication masters, multiple masters. Brief introduction to salt-cloud Overview, Setup AWS and salt-cloud, installing salt-cloud, cloud providers, cloud profiles, cloud maps, Introspection via salt cloud, Creating infrastructure, More information. Using vagrant to run Salt examples YAML.

This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.

Upskill your knowledge with Time Training Center’s Python Classes in Abu Dhabi.In this course you will master Python’s fundamental skills and web frameworks.Learn the core concepts of python such as data structures, algorithms and its  implementation. Enroll now! Call us: 97126713828 Mail : info@timetraining.ae Learn more:https://www.timetraining.ae/course/python-training-course Address: Office 203, ADCP Tower - B,Behind City Seasons, Electra Street, Abu Dhabi United Arab Emirates

Computer Science GCSE Syllabus The GCSE Computer Science Tutor Syllabus is designed to provide tutors in England with a comprehensive framework for teaching the GCSE Computer Science curriculum effectively. This syllabus aims to equip tutors with the necessary knowledge and skills to support students in their understanding and application of core computer science concepts.  Module 1: Introduction to Computer Science - Overview of computer science and its relevance in today's world - Understanding the components of a computer system - Introduction to algorithms and problem-solving techniques - Exploration of programming languages and their uses Module 2: Computer Hardware - Understanding the main components of a computer system, including CPU, memory, and storage devices - Exploring input and output devices and their functionalities - Understanding the role of operating systems and software in computer systems Module 3: Software Development - Introduction to programming concepts and languages (e.g., Python or Java) - Understanding variables, data types, and operators - Building algorithms and logical reasoning skills - Introduction to flowcharts and pseudocode - Implementation of simple programs and debugging techniques Module 4: Data Representation - Understanding binary, hexadecimal, and denary number systems - Representation of text, images, and sound using binary - Introduction to data compression and encryption techniques Module 5: Computer Networks - Understanding the basics of computer networks, including LAN, WAN, and the Internet - Introduction to network topologies, protocols, and security - Exploring the impact of digital communication on society Module 6: Cybersecurity and Ethical Issues - Understanding the importance of cybersecurity and data protection - Introduction to common threats and vulnerabilities - Exploring ethical issues related to computer science, such as privacy and intellectual property rights Module 7: Algorithms and Programming Techniques - Advanced programming concepts, including conditionals, loops, and functions - Introduction to sorting and searching algorithms - Exploring data structures, such as arrays and lists Module 8: System Architecture - Understanding the structure and function of a CPU - Introduction to memory hierarchy and cache - Exploring the Von Neumann architecture and its limitations Module 9: Computational Thinking and Problem Solving - Advanced problem-solving techniques using computational thinking - Introduction to algorithms for complex problems - Exploring algorithmic efficiency and optimization techniques Module 10: Exam Preparation and Revision - Reviewing key concepts covered throughout the syllabus - Practicing past exam questions and providing guidance on exam techniques - Supporting students with exam preparation strategies Please note that the duration and depth of each module can vary depending on the level of expertise required and the specific needs of the learners. Additionally, it's important to adapt the curriculum to the learners' proficiency levels, whether they are A Level/GCSE students or adult learners with different experience levels.

Our Economic and Financial Modelling courses are suitable for economists, researchers and regulators in policy making institutions such as central banks, ministries of finance, trade and investment, economic planning authorities, regional/international policy institutions, think tanks, petroleum industry and other business/economic sectors that make use of statistical and econometric modelling techniques.

Machine literacy in data wisdom is a fleetly expanding discipline and now is the crucial element. This groundbreaking field equips computers and systems with the capacity to learn from data and ameliorate their performance over time without unequivocal programming. Statistical ways are employed to train algorithms to produce groups or prognostications and to find significant findings in data mining systems. immaculately, the conclusions made from these perceptivity impact crucial growth pointers in operations and companies. What's Machine Learning? . Machine learning classes in pune The machine literacy term was chased by Arthur Samuel in 1959. It's the discipline solely concentrated on studying and erecting tools and ways that can let machines learn. These styles use data to enhance the computer performance of a particular set of tasks. Machine literacy algorithms induce prognostications or possibilities and produce a model grounded on data samples, also called training data. There's a need for machine literacy as these algorithms are applied in a broad range of operations, for illustration, computer vision, dispatch filtering, speech recognition, husbandry, and drugs, where it's a challenge to produce traditional algorithms that can negotiate the needed tasks. orders in Machine Learning Being such a vast and complicated field, machine literacy is divided into three different orders machine literacy orders Supervised literacy – In this system, the algorithm is trained using data that has been labeled and in which the target variable or asked result is known. Once trained, the algorithm may make prognostications grounded on unidentified information by learning how to associate input variables with the willed affair. Unsupervised literacy – In this case, the algorithm is trained on unlabeled data, and its thing is to discover structures or patterns within the data without having a specific target variable in mind. Common unsupervised literacy tasks include dimensionality reduction and clustering. underpinning literacy – An algorithm is trained via relations with the terrain in this type of literacy. The algorithm learns how to operate in order to maximize a price signal or negotiate a particular ideal. Through prices or penalties, it receives feedback that helps it upgrade its decision-making process. Artificial Intelligence and Machine Learning Artificial intelligence( AI) is divided into several subfields, and machine literacy( ML) is one of them. In order to produce intelligent machines that can pretend mortal intelligence, a variety of methodologies, approaches, and technologies are used. This notion is known as artificial intelligence( AI). The development of ways and models that allow computers to acquire knowledge from data and make recommendations or judgments without unequivocal programming is the focus of machine literacy( ML). Some academics were interested in the idea of having machines learn from data in the early stages of AI as an academic field. They tried to approach the issue using colorful emblematic ways and neural networks. They were primarily perceptrons, along with other models that were ultimately discovered to be reimaginings of the generalized direct models of statistics. For this case, you aim to make a system secerning cows and tykes. With the AI approach, you'll use ways to make a system that can understand the images with the help of specific features and rules you define. Machine literacy models will bear training using a particular dataset of pre-defined images. You need to give numerous farmlands of cows and tykes with corresponding markers. Why is Machine Learning Important? Machine literacy is an abecedarian subfield of artificial intelligence that focuses on assaying and interpreting patterns and structures in data. It enables logic, literacy, and decision-making outside of mortal commerce. The significance of machine literacy is expanding due to the extensively more expansive and more varied data sets, the availability and affordability of computational power, and the availability of high-speed internet. It facilitates the creation of new products and provides companies with a picture of trends in consumer geste and commercial functional patterns. Machine literacy is a high element of the business operations of numerous top enterprises, like Facebook, Google, and Uber. Prophetic Analytics Machine learning course in pune Machine literacy makes prophetic analytics possible by using data to read unborn results. It's salutary in the fields of finance, healthcare, marketing, and logistics. Associations may prognosticate customer growth, spot possible troubles, streamline operations, and take visionary action to ameliorate results using prophetic models. Personalization and recommendation systems Machine literacy makes recommendation systems and substantiated gests possible, impacting every aspect of our diurnal lives. Platforms like Netflix, Amazon, and Spotify use machine literacy algorithms to comprehend stoner preferences and offer substantiated recommendations. Personalization boosts stoner pleasure and engagement while promoting business expansion. Image and speech recognition Algorithms for machine literacy are particularly good at jobs like speech and picture recognition. Deep literacy, a branch of ML, has converted computer vision and natural language processing. It makes it possible for machines to comprehend, dissect, and produce visual and audio input. This technology is helpful for driverless vehicles, surveillance, medical imaging, and availability tools, among other effects. Machine learning training in pune

Trong kỷ nguyên số hiện nay, nhu cầu về lập trình viên full-stack với khả năng phát triển cả frontend lẫn backend ngày càng cao. FPT Aptech, một trong những trung tâm đào tạo lập trình viên quốc tế hàng đầu, mang đến khóa học full-stack được thiết kế chuyên biệt để đáp ứng yêu cầu này. Vậy khóa học full-stack tại FPT Aptech có gì đặc biệt và có thể giúp bạn trở thành lập trình viên quốc tế như thế nào? Hãy cùng khám phá trong bài viết dưới đây. 1. Tại sao nên chọn học tại FPT Aptech? Khóa học full-stack tại FPT Aptech cung cấp một chương trình đào tạo toàn diện, từ cơ bản đến nâng cao, giúp học viên trang bị đầy đủ các kỹ năng cần thiết để phát triển ứng dụng web hoàn chỉnh. Được thiết kế cho các lập trình viên quốc tế, khóa học không chỉ dạy các công nghệ phổ biến mà còn cập nhật các xu hướng mới nhất trong ngành. 2. Chương trình học toàn diện Khóa học full-stack tại FPT Aptech kéo dài trong 2 năm và được chia thành 4 học kỳ, bao gồm các môn học từ cơ bản đến nâng cao. Sinh viên sẽ được học các công nghệ frontend như HTML5, CSS3, và JavaScript, đồng thời làm quen với các framework như React và Angular. Về backend, chương trình đào tạo lập trình viên quốc tế Aptech bao gồm các ngôn ngữ và framework phổ biến như Node.js, PHP, và Django. Học kỳ 1: Thiết kế và phát triển website với HTML5, CSS3, JavaScript và các công cụ CMS. Học kỳ 2: Lập trình hướng đối tượng với Java SE và C#. Học kỳ 3: Công nghệ .NET, NodeJS và phân tích dữ liệu với Python. Học kỳ 4: Công nghệ Java EE và lập trình di động với Android và iOS. 70% thời lượng khóa học là thực hành, giúp học viên có cơ hội làm việc trên các dự án thực tế. Các eProject cuối mỗi học kỳ giúp sinh viên áp dụng kiến thức vào thực tiễn, xây dựng các ứng dụng web hoàn chỉnh và sẵn sàng cho công việc thực tế. Chương trình đào tạo lập trình viên full-stack tại FPT Aptech tuyển sinh các bạn trẻ đam mê công nghệ thông tin, Hệ thống đào tạo lập trình viên quốc tế Aptech từ học sinh trung học phổ thông đến sinh viên đại học và người đi làm muốn chuyển nghề. Chỉ cần bạn có đam mê với lập trình và mong muốn phát triển trong lĩnh vực này, Aptech sẽ là nơi giúp bạn hiện thực hóa ước mơ. 3. Đội ngũ giảng viên chất lượng cao FPT Aptech tự hào với đội ngũ giảng viên là các chuyên gia giàu kinh nghiệm trong ngành công nghệ thông tin. Họ không chỉ giảng dạy lý thuyết mà còn chia sẻ những kinh nghiệm thực tế quý báu. Với sự hướng dẫn của các giảng viên, sinh viên sẽ có cơ hội học hỏi từ những người đã thành công trong lĩnh vực lập trình và phát triển phần mềm. 4. Cơ hội nghề nghiệp quốc tế Sau khi hoàn thành khóa học, học viên sẽ nhận bằng Advanced Diploma in Full-Stack Development từ Tập đoàn Aptech, trường Aptech có giá trị toàn cầu. Điều này giúp mở rộng cơ hội việc làm không chỉ tại Việt Nam mà còn ở nhiều quốc gia khác. Ngoài ra, FPT Aptech cung cấp dịch vụ hỗ trợ việc làm, bao gồm ưu tiên thực tập và giới thiệu việc làm tại các công ty thuộc Tập đoàn FPT và các đối tác liên kết. Học viên có thể tiếp cận nhiều cơ hội việc làm và thực tập tại các công ty công nghệ hàng đầu. 5. Học bổng hỗ trợ FPT Aptech luôn chú trọng đến việc hỗ trợ học viên, đặc biệt là về tài chính. Một số chương trình tại đây bao gồm: Học bổng 12 năm đèn sách: Dành cho những bạn học sinh có thành tích tốt trong 12 năm học Học bổng tập làm Dev: Học bổng dành cho các bạn học sinh, sinh viên, người đi làm mong muốn chuyển ngành quan tâm đến ngành Công nghệ thông tin – Lập trình Ưu đãi học phí cho “Bộ đội xuất ngũ và Dân quân tự vệ”: Ưu đãi dành cho đối tượng bộ đội sau xuất ngũ hay dân quân tự vệ tìm kiếm tương lai mới với ngành lập trình Khóa học full-stack tại FPT Aptech không chỉ trang bị cho học viên những kiến thức và kỹ năng cần thiết để trở thành lập trình viên quốc tế mà còn mở ra cơ hội nghề nghiệp rộng lớn trên toàn cầu. Đừng quên để lại bình luận và theo dõi trang của chúng tôi để cập nhật những thông tin mới nhất từ FPT Aptech.