993 Courses

Learn to design, plan, and scale cloud implementations with Google Cloud Platform's BigQuery. This course will walk you through the fundamentals of applied machine learning and BigQuery ML along with its history, architecture, and use cases.

Duration 4 Days 24 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brand-new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm ? YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 5 Days 30 CPD hours This course is intended for This intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers who want to leverage Scala and Spark to tackle complex data challenges and develop scalable, high-performance applications across diverse domains. Practical programming experience is required to participate in the hands-on labs. Overview Working in a hands-on learning environment led by our expert instructor you'll: Develop a basic understanding of Scala and Apache Spark fundamentals, enabling you to confidently create scalable and high-performance applications. Learn how to process large datasets efficiently, helping you handle complex data challenges and make data-driven decisions. Gain hands-on experience with real-time data streaming, allowing you to manage and analyze data as it flows into your applications. Acquire practical knowledge of machine learning algorithms using Spark MLlib, empowering you to create intelligent applications and uncover hidden insights. Master graph processing with GraphX, enabling you to analyze and visualize complex relationships in your data. Discover generative AI technologies using GPT with Spark and Scala, opening up new possibilities for automating content generation and enhancing data analysis. Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.Guided by our expert instructor, you?ll explore the fundamentals of Scala programming and Apache Spark while gaining valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You?ll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems. Introduction to Scala Brief history and motivation Differences between Scala and Java Basic Scala syntax and constructs Scala's functional programming features Introduction to Apache Spark Overview and history Spark components and architecture Spark ecosystem Comparing Spark with other big data frameworks Basics of Spark Programming SparkContext and SparkSession Resilient Distributed Datasets (RDDs) Transformations and Actions Working with DataFrames Spark SQL and Data Sources Spark SQL library and its advantages Structured and semi-structured data sources Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.) Data manipulation using SQL queries Basic RDD Operations Creating and manipulating RDDs Common transformations and actions on RDDs Working with key-value data Basic DataFrame and Dataset Operations Creating and manipulating DataFrames and Datasets Column operations and functions Filtering, sorting, and aggregating data Introduction to Spark Streaming Overview of Spark Streaming Discretized Stream (DStream) operations Windowed operations and stateful processing Performance Optimization Basics Best practices for efficient Spark code Broadcast variables and accumulators Monitoring Spark applications Integrating External Libraries and Tools, Spark Streaming Using popular external libraries, such as Hadoop and HBase Integrating with cloud platforms: AWS, Azure, GCP Connecting to data storage systems: HDFS, S3, Cassandra, etc. Introduction to Machine Learning Basics Overview of machine learning Supervised and unsupervised learning Common algorithms and use cases Introduction to Spark MLlib Overview of Spark MLlib MLlib's algorithms and utilities Data preparation and feature extraction Linear Regression and Classification Linear regression algorithm Logistic regression for classification Model evaluation and performance metrics Clustering Algorithms Overview of clustering algorithms K-means clustering Model evaluation and performance metrics Collaborative Filtering and Recommendation Systems Overview of recommendation systems Collaborative filtering techniques Implementing recommendations with Spark MLlib Introduction to Graph Processing Overview of graph processing Use cases and applications of graph processing Graph representations and operations Introduction to Spark GraphX Overview of GraphX Creating and transforming graphs Graph algorithms in GraphX Big Data Innovation! Using GPT and Generative AI Technologies with Spark and Scala Overview of generative AI technologies Integrating GPT with Spark and Scala Practical applications and use cases Bonus Topics / Time Permitting Introduction to Spark NLP Overview of Spark NLP Preprocessing text data Text classification and sentiment analysis Putting It All Together Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.

The course focuses on the five domains that should be known for the CompTIA PenTest+ PT0-002 exam. Learn to successfully plan and scope a pen test engagement with a client, find vulnerabilities, exploit them to get into a network, then report on those findings to the client with the help of this comprehensive course.

Master DeepSeek AI with this CPD-accredited course! Learn automation, coding, and business solutions to boost productivity and career growth.

Learn how you can develop and deploy Java, Python, NodeJS Lambda Functions and manage them using Python and Boto3!

The comprehensive Complete U&P AI - Natural Language Processing (NLP) with Python has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the Complete U&P AI - Natural Language Processing (NLP) with Python today, and learn from the very best the industry has to offer! This best selling Complete U&P AI - Natural Language Processing (NLP) with Python has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Complete U&P AI - Natural Language Processing (NLP) with Python is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The Complete U&P AI - Natural Language Processing (NLP) with Python is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The Complete U&P AI - Natural Language Processing (NLP) with Python is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn. After successfully completing the Complete U&P AI - Natural Language Processing (NLP) with Python, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Complete U&P AI - Natural Language Processing (NLP) with Python will help you stand out from the crowd. You can also validate your certification on our website. We know that you are busy and that time is precious, so we have designed the Complete U&P AI - Natural Language Processing (NLP) with Python to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device.  Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.

Get up to speed with automating repetitive tasks with Python

In this competitive job market, you need to have some specific skills and knowledge to start your career and establish your position. This Machine Learning Project - Auto Image Captioning for Social Media will help you understand the current demands, trends and skills in the sector. The course will provide you with the essential skills you need to boost your career growth in no time. The Machine Learning Project - Auto Image Captioning for Social Media will give you clear insight and understanding about your roles and responsibilities, job perspective and future opportunities in this field. You will be familiarised with various actionable techniques, career mindset, regulations and how to work efficiently. This course is designed to provide an introduction to Machine Learning Project - Auto Image Captioning for Social Media and offers an excellent way to gain the vital skills and confidence to work toward a successful career. It also provides access to proven educational knowledge about the subject and will support those wanting to attain personal goals in this area. Learning Objectives Learn the fundamental skills you require to be an expert Explore different techniques used by professionals Find out the relevant job skills & knowledge to excel in this profession Get a clear understanding of the job market and current demand Update your skills and fill any knowledge gap to compete in the relevant industry CPD accreditation for proof of acquired skills and knowledge Who is this Course for? Whether you are a beginner or an existing practitioner, our CPD accredited Machine Learning Project - Auto Image Captioning for Social Media is perfect for you to gain extensive knowledge about different aspects of the relevant industry to hone your skill further. It is also great for working professionals who have acquired practical experience but require theoretical knowledge with a credential to support their skill, as we offer CPD accredited certification to boost up your resume and promotion prospects. Entry Requirement Anyone interested in learning more about this subject should take this Machine Learning Project - Auto Image Captioning for Social Media. This course will help you grasp the basic concepts as well as develop a thorough understanding of the subject. The course is open to students from any academic background, as there is no prerequisites to enrol on this course. The course materials are accessible from an internet enabled device at anytime of the day. CPD Certificate from Course Gate At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for £9 and the hard copy for £15. Also, you can order both PDF and hardcopy certificates for £22. Career path The Machine Learning Project - Auto Image Captioning for Social Media will help you to enhance your knowledge and skill in this sector. After accomplishing this course, you will enrich and improve yourself and brighten up your career in the relevant job market. Course Curriculum Section 01: Introduction Introduction to Course 00:05:00 Section 02: Building the Auto Image Captioning Import the Libraries 00:09:00 Accessing the Caption Dataset for Training 00:05:00 Accessing the Image DataSet for Training 00:02:00 Preprocessing the Text Data 00:11:00 Pre-Process and Load Captions Data 00:11:00 Loading the Captions for Training and Test Data 00:04:00 Preprocessing of Image Data 00:11:00 Loading Features for Train and Test Dataset 00:09:00 Text Tokenization and Sequence Text 00:11:00 Data Generators 00:11:00 Define the Model 00:03:00 Evaluation of Model 00:09:00 Test the Model 00:08:00 Section 03: Deployment of Machine Learning App Create Streamlit App 00:10:00 Streamlit Prediction 00:06:00 Test Streamlit App 00:03:00 Deploy Streamlit on AWS EC2 Instance 00:09:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

In an era awash with data, understanding it is the key to unlocking significant opportunities. Enter the realm of 'SQL For Data Analytics & Database Development'. Dive deep into the heart of data manipulation, exploration, and insight generation. This course unfurls the magic behind SQL, drawing back the curtain on the tools that empower businesses globally. Understanding SQL's profound capabilities opens doors to a world where data-driven decision-making is not just an advantage but an imperative. It isn't simply about data storage. This course unravels the art of analytics, shedding light on how to glean valuable insights from vast data lakes. The path of SQL isn't merely technical; it's the spine of transformative decisions in today's leading industries. Offering a systematic approach to database development, we invite you to embark on this illuminative journey, stitching the threads of raw data into the fabric of meaningful stories. Come harness the power of SQL. Whether your intent is data analytics or the intricate craft of database development, this is your gateway. Let us guide you, from the rudimentary steps to mastering advanced commands, constructing your data narrative, and informing the future. Learning Outcomes: Comprehend the fundamental architecture of SQL and its environment. Acquire proficiency in basic and advanced SQL statements. Understand and implement GROUP BY statements for data aggregation. Master the concepts and applications of JOINS in databases. Cultivate the ability to create and structure databases and tables. Delve into advanced SQL commands, enhancing data manipulation and querying capabilities. Construct efficient database models, fostering optimal data storage and retrieval.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/SQL-DATA-ANALYSIS.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why choose this SQL For Data Analytics & Database Development course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the SQL For Data Analytics & Database Development Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this SQL For Data Analytics & Database Development course for? Aspirants seeking to transition into data-driven roles in various industries. Database administrators aiming to broaden their analytical capabilities. Business analysts eager to enhance their data querying skills. Researchers in need of comprehensive data management tools. Tech enthusiasts wanting to grasp the underpinnings of database systems. Career path Data Analyst - Average salary: £35,000 - £50,000 Per Annum Database Developer - Average salary: £40,000 - £55,000 Per Annum Business Intelligence Analyst - Average salary: £38,000 - £52,000 Per Annum SQL Developer - Average salary: £42,000 - £58,000 Per Annum Database Administrator (DBA) - Average salary: £45,000 - £60,000 Per Annum Data Engineer - Average salary: £47,000 - £63,000 Per Annum Prerequisites This SQL For Data Analytics & Database Development was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Course Introduction Introduction 00:04:00 Course Curriculum Overview 00:05:00 Overview of Databases 00:10:00 SQL Environment Setup MySQL Installation 00:16:00 MySQL Workbench Installation 00:09:00 Connecting to MySQL using Console 00:09:00 SQL Statement Basics Overview of Challenges 00:04:00 SQL Statement Basic 00:16:00 SELECT Statement 00:09:00 SELECT DISTINCT 00:05:00 Column AS Statement 00:12:00 COUNT built-in Method usage 00:11:00 SELECT WHERE Clause - Part One 00:05:00 SELECT WHERE Clause - Part Two 00:11:00 SQL Statement Basic 00:16:00 SQL Limit Clause Statement 00:09:00 SQL Using BETWEEN with Same Column Data 00:11:00 How to Apply IN Operator 00:11:00 Wildcard Characters with LIKE and ILIKE 00:11:00 GROUP BY Statements Overview of GROUP BY 00:06:00 Aggregation function SUM() 00:09:00 Aggregation MIN() and MAX() 00:05:00 GROUP BY - One 00:09:00 GROUP BY - Two 00:12:00 HAVING Clause 00:05:00 JOINS Overview of JOINS 00:04:00 Introduction to JOINS 00:04:00 AS Statement table 00:03:00 INNER Joins 00:14:00 FULL Outer Join 00:11:00 LEFT Outer JOIN 00:08:00 RIGHT JOIN 00:08:00 Union 00:07:00 Advanced SQL Commands / Statements Timestamps 00:12:00 EXTRACT from timestamp 00:10:00 Mathematical Functions 00:12:00 String Functions 00:22:00 SUBQUERY 00:13:00 Creating Database and Tables Basic of Database and Tables 00:06:00 DataTypes 00:10:00 Primarykey and Foreignkey 00:06:00 Create Table in SQL Script 00:13:00 Insert 00:11:00 Update 00:07:00 Delete 00:04:00 Alter Table 00:09:00 Drop Table 00:05:00 NOT NULL Constraint 00:08:00 UNIQUE Constraint 00:09:00 Databases and Tables Creating a Database backup 00:12:00 10a Overview of Databases and Tables 00:05:00 10c Restoring a Database 00:07:00