979 Data Science courses delivered Online

S3 is by far the most popular AWS service out there and the demand is only increasing! Most of the Fortune 500 companies, mid-size companies, and start-ups are making use of it heavily! In this course, you will learn the ins and outs of S3 and how to implement solutions with S3.

Description Register on the Deep Learning & Neural Networks Python - Keras today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a certificate as proof of your course completion. The Deep Learning & Neural Networks Python - Keras course is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablets, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With This Course Receive a digital certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment You need to attend an assessment right after the completion of this course to evaluate your progression. For passing the assessment, you need to score at least 60%. After submitting your assessment, you will get feedback from our experts immediately. Who Is This Course For The course is ideal for those who already work in this sector or are aspiring professionals. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.   Course Content Course Introduction And Table Of Contents Course Introduction and Table of Contents 00:11:00 Deep Learning Overview Deep Learning Overview - Theory Session - Part 1 00:06:00 Deep Learning Overview - Theory Session - Part 2 00:07:00 Choosing Between ML Or DL For The Next AI Project - Quick Theory Session Choosing Between ML or DL for the next AI project - Quick Theory Session 00:09:00 Preparing Your Computer Preparing Your Computer - Part 1 00:07:00 Preparing Your Computer - Part 2 00:06:00 Python Basics Python Basics - Assignment 00:09:00 Python Basics - Flow Control 00:09:00 Python Basics - Functions 00:04:00 Python Basics - Data Structures 00:12:00 Theano Library Installation And Sample Program To Test Theano Library Installation and Sample Program to Test 00:11:00 TensorFlow Library Installation And Sample Program To Test TensorFlow library Installation and Sample Program to Test 00:09:00 Keras Installation And Switching Theano And TensorFlow Backends Keras Installation and Switching Theano and TensorFlow Backends 00:10:00 Explaining Multi-Layer Perceptron Concepts Explaining Multi-Layer Perceptron Concepts 00:03:00 Explaining Neural Networks Steps And Terminology Explaining Neural Networks Steps and Terminology 00:10:00 First Neural Network With Keras - Understanding Pima Indian Diabetes Dataset First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset 00:07:00 Explaining Training And Evaluation Concepts Explaining Training and Evaluation Concepts 00:11:00 Pima Indian Model - Steps Explained Pima Indian Model - Steps Explained - Part 1 00:09:00 Pima Indian Model - Steps Explained - Part 2 00:07:00 Coding The Pima Indian Model Coding the Pima Indian Model - Part 1 00:11:00 Coding the Pima Indian Model - Part 2 00:09:00 Pima Indian Model - Performance Evaluation Pima Indian Model - Performance Evaluation - Automatic Verification 00:06:00 Pima Indian Model - Performance Evaluation - Manual Verification 00:08:00 Pima Indian Model - Performance Evaluation - K-Fold Validation - Keras Pima Indian Model - Performance Evaluation - k-fold Validation - Keras 00:10:00 Pima Indian Model - Performance Evaluation - Hyper Parameters Pima Indian Model - Performance Evaluation - Hyper Parameters 00:12:00 Understanding Iris Flower Multi-Class Dataset Understanding Iris Flower Multi-Class Dataset 00:08:00 Developing The Iris Flower Multi-Class Model Developing the Iris Flower Multi-Class Model - Part 1 00:09:00 Developing the Iris Flower Multi-Class Model - Part 2 00:06:00 Developing the Iris Flower Multi-Class Model - Part 3 00:09:00 Understanding The Sonar Returns Dataset Understanding the Sonar Returns Dataset 00:07:00 Developing The Sonar Returns Model Developing the Sonar Returns Model 00:10:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Data Preparation - Standardization 00:15:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Layer Tuning for Smaller Network 00:07:00 Sonar Performance Improvement - Layer Tuning For Larger Network Sonar Performance Improvement - Layer Tuning for Larger Network 00:06:00 Understanding The Boston Housing Regression Dataset Understanding the Boston Housing Regression Dataset 00:07:00 Developing The Boston Housing Baseline Model Developing the Boston Housing Baseline Model 00:08:00 Boston Performance Improvement By Standardization Boston Performance Improvement by Standardization 00:07:00 Boston Performance Improvement By Deeper Network Tuning Boston Performance Improvement by Deeper Network Tuning 00:05:00 Boston Performance Improvement By Wider Network Tuning Boston Performance Improvement by Wider Network Tuning 00:04:00 Save & Load The Trained Model As JSON File (Pima Indian Dataset) Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 1 00:09:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 2 00:08:00 Save And Load Model As YAML File - Pima Indian Dataset Save and Load Model as YAML File - Pima Indian Dataset 00:05:00 Load And Predict Using The Pima Indian Diabetes Model Load and Predict using the Pima Indian Diabetes Model 00:09:00 Load And Predict Using The Iris Flower Multi-Class Model Load and Predict using the Iris Flower Multi-Class Model 00:08:00 Load And Predict Using The Sonar Returns Model Load and Predict using the Sonar Returns Model 00:10:00 Load And Predict Using The Boston Housing Regression Model Load and Predict using the Boston Housing Regression Model 00:08:00 An Introduction To Checkpointing An Introduction to Checkpointing 00:06:00 Checkpoint Neural Network Model Improvements Checkpoint Neural Network Model Improvements 00:10:00 Checkpoint Neural Network Best Model Checkpoint Neural Network Best Model 00:04:00 Loading The Saved Checkpoint Loading the Saved Checkpoint 00:05:00 Plotting Model Behavior History Plotting Model Behavior History - Introduction 00:06:00 Plotting Model Behavior History - Coding 00:08:00 Dropout Regularization - Visible Layer Dropout Regularization - Visible Layer - Part 1 00:11:00 Dropout Regularization - Visible Layer - Part 2 00:06:00 Dropout Regularization - Hidden Layer Dropout Regularization - Hidden Layer 00:06:00 Learning Rate Schedule Using Ionosphere Dataset - Intro Learning Rate Schedule using Ionosphere Dataset 00:06:00 Time Based Learning Rate Schedule Time Based Learning Rate Schedule - Part 1 00:07:00 Time Based Learning Rate Schedule - Part 2 00:12:00 Drop Based Learning Rate Schedule Drop Based Learning Rate Schedule - Part 1 00:07:00 Drop Based Learning Rate Schedule - Part 2 00:08:00 Convolutional Neural Networks - Introduction Convolutional Neural Networks - Part 1 00:11:00 Convolutional Neural Networks - Part 2 00:06:00 MNIST Handwritten Digit Recognition Dataset Introduction to MNIST Handwritten Digit Recognition Dataset 00:06:00 Downloading and Testing MNIST Handwritten Digit Recognition Dataset 00:10:00 MNIST Handwritten Digit Recognition Dataset MNIST Multi-Layer Perceptron Model Development - Part 1 00:11:00 MNIST Multi-Layer Perceptron Model Development - Part 2 00:06:00 Convolutional Neural Network Model Using MNIST Convolutional Neural Network Model using MNIST - Part 1 00:13:00 Convolutional Neural Network Model using MNIST - Part 2 00:12:00 Large CNN Using MNIST Large CNN using MNIST 00:09:00 Load And Predict Using The MNIST CNN Model Load and Predict using the MNIST CNN Model 00:14:00 Introduction To Image Augmentation Using Keras Introduction to Image Augmentation using Keras 00:11:00 Augmentation Using Sample Wise Standardization Augmentation using Sample Wise Standardization 00:10:00 Augmentation Using Feature Wise Standardization & ZCA Whitening Augmentation using Feature Wise Standardization & ZCA Whitening 00:04:00 Augmentation Using Rotation And Flipping Augmentation using Rotation and Flipping 00:04:00 Saving Augmentation Saving Augmentation 00:05:00 CIFAR-10 Object Recognition Dataset - Understanding And Loading CIFAR-10 Object Recognition Dataset - Understanding and Loading 00:12:00 Simple CNN Using CIFAR-10 Dataset Simple CNN using CIFAR-10 Dataset - Part 1 00:09:00 Simple CNN using CIFAR-10 Dataset - Part 2 00:06:00 Simple CNN using CIFAR-10 Dataset - Part 3 00:08:00 Train And Save CIFAR-10 Model Train and Save CIFAR-10 Model 00:08:00 Load And Predict Using CIFAR-10 CNN Model Load and Predict using CIFAR-10 CNN Model 00:16:00 RECOMENDED READINGS Recomended Readings 00:00:00

Course Overview: According to the World Economic Forum, data analysts will be among the most in-demand professions by 2025. This Basic Google Data Studio course takes you on an enlightening journey, illuminating the intricate world of Google Data Studio from the ground up.The Basic Google Data Studio course is your stepping stone into data visualisation, geo-visualization, and in-depth socio-economic analysis. With four comprehensive modules, this curriculum is crafted to impart the foundational principles and techniques of Google Data Studio, ensuring learners possess the proficiency to translate raw data into meaningful insights.Enrol Today and Start Learning! Key Features of the Course: The Basic Google Data Studio course boasts an array of appealing features, including a CPD certificate upon completion, marking your journey into mastering Google Data Studio. 24/7 Learning Assistance ensures you can absorb the course material at your own pace, whenever it suits you best. Expect exciting learning materials that make mastering data visualisation a stimulating and enjoyable endeavour. Who is This Course For? This Basic Google Data Studio course is designed for anyone inclined towards data and interested in visual storytelling. Whether you're a business owner looking to make informed decisions, a student eyeing a future in data analysis, or a data enthusiast, this course could be the perfect fit. What You Will Learn: Introduction to Google Data Studio and its features. Navigation and interface overview of Google Data Studio. Creating reports using different data sources. Converting data into visually appealing graphs and charts. Exploring geographic data visualisation techniques. Uncovering hidden geographic trends through data visualisation. Applying the learned skills to real-world socio-economic case studies. Why Enrol in This Course: This Basic Google Data Studio course consistently receives top reviews from its participants. Recently updated with the latest trends and practices in data visualisation, this course ensures you stay on top of industry shifts. By enrolling in this course, you will develop indispensable skills in data analysis and visual storytelling. Requirements: This course requires a fundamental understanding of data analysis concepts. Internet access is required to practise Google Data Studio and access course materials. Career Path: Upon completing this Basic Google Data Studio course, you can look forward to opportunities in various data-focused professions. Such as Data Analyst Business Intelligence Developer Marketing Analyst SEO Specialist Data Scientist Data Visualisation Specialist Report Analyst In the UK, these roles offer attractive salary packages ranging from £25,000 for entry-level positions to over £60,000+ for more advanced roles. Certification: Upon successful completion of the Basic Google Data Studio course, you will be awarded a CPD certificate as proof of your proficiency in Google Data Studio. Course Curriculum 1 sections • 4 lectures • 02:41:00 total length •Module 01: Introduction to GDS: 00:36:00 •Module 02: Data Visualization: 01:29:00 •Module 03: Geo-visualization: 00:16:00 •Module 04: A Socio-Economic Case Study: 00:20:00

Overview This comprehensive course on Google Data Studio: Data Analytics will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Google Data Studio: Data Analytics comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Google Data Studio: Data Analytics. It is available to all students, of all academic backgrounds. Requirements Our Google Data Studio: Data Analytics is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 4 sections • 17 lectures • 02:32:00 total length •Course Overview: 00:01:00 •Format Data in Google Sheets: 00:08:00 •Sheet Functions 1: Query & Import Range: 00:07:00 •Sheets Function 2: Vlookup & Defined Range: 00:10:00 •Sheets Function 3: Cross Table Calculations: 00:09:00 •Connect Data to Google Data Studio: 00:04:00 •GDS Calculated Fields: 00:08:00 •GDS Theme Customization: 00:07:00 •GDS Page Layout Design: 00:17:00 •GDS Charts: Scorecards: 00:12:00 •GDS Charts: Time Series Graphs: 00:09:00 •GDS Blending and Joining Data Tables: 00:07:00 •GDS Charts: Bar, Donut, and Treemap: 00:17:00 •GDS Charts: Interactive Filters: 00:08:00 •GDS Project Page Completion: 00:17:00 •GDS Client Page Completion: 00:11:00 •Additional Resources - Google Data Studio: Data Analytics: 00:00:00

In a world of big data, statistical analysis is no longer a luxury, it's a necessity. Whether you're a seasoned professional or just starting out, our "Measuring Central Tendency and Dispersion" course is a must-have tool in your analytical arsenal. With comprehensive modules covering everything from introduction to statistics to common statistical mistakes, you'll gain a deep understanding of how to measure and interpret data, making you a valuable asset to any organisation. Enrol now and take your analytical skills to the next level! Learning Outcomes: After completing the course, you can expect to: Understand statistical analysis and its importance in decision-making. Learn how to measure central tendency and dispersion accurately. Gain knowledge about correlation and regression analysis, probability, and hypothesis testing. Acquire skills in creating charts and graphs for data visualisation. Identify and avoid common statistical mistakes. Develop a strong foundation in statistical analysis to apply in future studies and career. In today's data-driven world, a strong understanding of statistics is crucial for professionals across industries. Our comprehensive Statistics course is designed to equip learners with the foundational knowledge and skills necessary for effective statistical analysis. With modules covering a range of statistical concepts, including measuring central tendency and dispersion, probability, hypothesis testing, and more, this course provides an in-depth exploration of the principles that underpin statistical analysis. Whether you're a business professional looking to make data-driven decisions or a student preparing for further study in statistics, this course offers a comprehensive overview of statistical analysis. Our course materials provide a theoretical foundation that can be applied to a range of real-world situations, helping learners to develop a strong understanding of the concepts that underpin statistical analysis. Certification Upon completion of the course, learners can obtain a certificate as proof of their achievement. You can receive a £4.99 PDF Certificate sent via email, a £9.99 Printed Hardcopy Certificate for delivery in the UK, or a £19.99 Printed Hardcopy Certificate for international delivery. Each option depends on individual preferences and locations. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This course is ideal for the following: Business professionals looking to improve their data analysis skills. Students preparing for further study in statistics or related fields. Anyone with an interest in statistical analysis. Career path This course will be helpful for anyone looking to pursue a career as: Statistical Analyst: £23,000-£40,000 per year. Data Analyst: £24,000-£45,000 per year. Business Analyst: £25,000-£50,000 per year. Market Research Analyst: £24,000-£40,000 per year. Financial Analyst: £26,000-£55,000 per year. Actuary: £30,000-£70,000 per year.

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Thinking about learning Big Data? The Big Data for Business course teaches learners to understand how to manage Big Data and its use with Machine Learning. 93% off until August 31 2024.

In this course, we will be using Django 3 to build 3 stunning websites with HTML5, CSS3, and Bootstrap 4. This format will allow you to learn Django and not just follow along like a robot. We will use Python in this course, so if you have never used Python before, we will start with a Python refresher to get you up to speed (no other Python experience required).

This is a hands-on comprehensive course for beginners and in just two hours, you will learn the fundamentals of the Hadoop Ecosystem and its three main building blocks. This course will prepare you to start learning more about big data and to implement Hadoop components in Azure Cloud using HDInsight.

QLS Endorsed + CPD QS Accredited - Dual Certification | Instant Access | 24/7 Tutor Support | All-Inclusive Cost