1323 Scientist courses

Dive into the revolutionary world of AI image generation with our Mastering Dall-E course. From understanding diffusion models to harnessing Dall-E for creative and commercial use, this course offers a comprehensive guide to mastering this cutting-edge technology.

NLP Practitioner Diploma is one of our best selling and most popular course. The NLP Practitioner Diploma is organised into 02 modules and includes everything you need to become successful in this profession. To make this course more accessible for you, we have designed it for both part-time and full-time students. You can study at your own pace or become an expert in just 4hours! If you require support, our experienced tutors are always available to help you throughout the comprehensive syllabus of this course and answer all your queries through email. Why choose this course Earn an e-certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Benefit from instant feedback through mock exams and multiple-choice assessments Get 24/7 help or advice from our email and live chat teams Full Tutor Support on Weekdays Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Mock exams Multiple-choice assessment Certification 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. Who is this course for? NLP Practitioner Diploma is suitable for anyone who want to gain extensive knowledge, potential experience and professional skills in the related field. This is a great opportunity for all student from any academic backgrounds to learn more on this subject.

Unlock the secrets of crime investigation with our Forensic Science Course: Exploring Crime Background. Dive deep into the world of fingerprint and DNA analysis, crime scene investigation, toxicology, arson, and more. Gain practical skills and real-world insights, preparing you for a rewarding career in forensic sciences. Join us to explore the science behind solving mysteries and contributing to justice. Enroll now for an immersive learning experience!

This Professional Certificate Course in Data Collection and Analysis offers a holistic understanding of best practices, covering digital data organization, analytics tool utilization, and effective data visualization. Participants will master strategies for collecting diverse digital channel data and gain skills in analyzing and interpreting insights for informed decision-making. After the successful completion of the course, you will be able to learn about the following: Best practices for collecting and organizing digital data How to use digital analytics tools to analyze data and gain insights Data visualization techniques and tools for presenting data effectively Strategies for collecting data from different digital channels, including social media, email, and mobile apps Best practices for analyzing and interpreting data to drive actionable insights This Professional Certificate Course in Data Collection and Analysis offers a comprehensive understanding of best practices in collecting and organizing digital data. Participants will learn to utilize digital analytics tools, master data visualization techniques, and employ strategies for collecting data from diverse digital channels, including social media and mobile apps. The course emphasizes interpreting data to derive actionable insights, empowering learners with practical skills for informed decision-making. This Professional Certificate Course in Data Collection and Analysis provides a comprehensive understanding of best practices in collecting, organizing, and analyzing digital data. Participants will learn to utilize digital analytics tools, master data visualization techniques, and develop strategies for collecting data from various digital channels, including social media and mobile apps. The course emphasizes interpreting data to derive actionable insights, empowering individuals with practical skills for informed decision-making. Course Structure and Assessment Guidelines Watch this video to gain further insight. Navigating the MSBM Study Portal Watch this video to gain further insight. Interacting with Lectures/Learning Components Watch this video to gain further insight. Data Collection and Analysis Self-paced pre-recorded learning content on this topic. Data Collection And Analysis Put your knowledge to the test with this quiz. Read each question carefully and choose the response that you feel is correct. All MSBM courses are accredited by the relevant partners and awarding bodies. Please refer to MSBM accreditation in about us for more details. There are no strict entry requirements for this course. Work experience will be added advantage to understanding the content of the course.The certificate is designed to enhance the learner's knowledge in the field. This certificate is for everyone eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience, Data Analysts and Scientists Marketing Professionals Business Intelligence Specialists Digital Marketing Managers Researchers and Academics Information Technology Professionals Decision-makers and Strategists Social Media Managers Mobile App Developers Email Marketing Specialists Average Completion Time 2 Weeks Accreditation 3 CPD Hours Level Advanced Start Time Anytime 100% Online Study online with ease. Unlimited Access 24/7 unlimited access with pre-recorded lectures. Low Fees Our fees are low and easy to pay online.

Duration 0.5 Days 3 CPD hours This course is intended for This course is designed for business leaders and decision makers, including C-level executives, project managers, HR leaders, Marketing and Sales leaders, and technical sales consultants, who want to increase their knowledge of and familiarity with concepts surrounding data science. Other individuals who want to know more about basic data science concepts are also candidates for this course. This course is also designed to assist learners in preparing for the CertNexus DSBIZ™ (Exam DSZ-110) credential. Overview In this course, you will identify how data science supports business decisions. You will: Explain the fundamentals of data science Describe common implementations of data science. Identify the impact data science can have on a business The ability to identify and respond to changing trends is a hallmark of a successful business. Whether those trends are related to customers and sales or to regulatory and industry standards, businesses are wise to keep track of the variables that can affect the bottom line. In today's business landscape, data comes from numerous sources and in diverse forms. By leveraging data science concepts and technologies, businesses can mold all of that raw data into information that facilitates decisions to improve and expand the success of the business. Data Science Fundamentals What is Data Science? Types of Data Data Science Roles Data Science Implementation The Data Science Lifecycle Data Acquisition and Preparation Data Modeling and Visualization The Impact of Data Science Benefits of Data Science Challenges of Data Science Business Use Cases for Data Science Additional course details: Nexus Humans CertNexus Data Science for Business Professionals (DSBIZ) 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 CertNexus Data Science for Business Professionals (DSBIZ) 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 2 Days 12 CPD hours This course is intended for Anyone who works with IBM SPSS Statistics and wants to learn advanced statistical procedures to be able to better answer research questions. Overview Introduction to advanced statistical analysis Group variables: Factor Analysis and Principal Components Analysis Group similar cases: Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Predict categorical targets with Discriminant Analysis Predict categorical targets with Logistic Regression Predict categorical targets with Decision Trees Introduction to Survival Analysis Introduction to Generalized Linear Models Introduction to Linear Mixed Models This course provides an application-oriented introduction to advanced statistical methods available in IBM SPSS Statistics. Students will review a variety of advanced statistical techniques and discuss situations in which each technique would be used, the assumptions made by each method, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for predicting variables, as well as methods to cluster variables and cases. Introduction to advanced statistical analysis Taxonomy of models Overview of supervised models Overview of models to create natural groupings Group variables: Factor Analysis and Principal Components Analysis Factor Analysis basics Principal Components basics Assumptions of Factor Analysis Key issues in Factor Analysis Improve the interpretability Use Factor and component scores Group similar cases: Cluster Analysis Cluster Analysis basics Key issues in Cluster Analysis K-Means Cluster Analysis Assumptions of K-Means Cluster Analysis TwoStep Cluster Analysis Assumptions of TwoStep Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Nearest Neighbor Analysis basics Key issues in Nearest Neighbor Analysis Assess model fit Predict categorical targets with Discriminant Analysis Discriminant Analysis basics The Discriminant Analysis model Core concepts of Discriminant Analysis Classification of cases Assumptions of Discriminant Analysis Validate the solution Predict categorical targets with Logistic Regression Binary Logistic Regression basics The Binary Logistic Regression model Multinomial Logistic Regression basics Assumptions of Logistic Regression procedures Testing hypotheses Predict categorical targets with Decision Trees Decision Trees basics Validate the solution Explore CHAID Explore CRT Comparing Decision Trees methods Introduction to Survival Analysis Survival Analysis basics Kaplan-Meier Analysis Assumptions of Kaplan-Meier Analysis Cox Regression Assumptions of Cox Regression Introduction to Generalized Linear Models Generalized Linear Models basics Available distributions Available link functions Introduction to Linear Mixed Models Linear Mixed Models basics Hierachical Linear Models Modeling strategy Assumptions of Linear Mixed Models Additional course details: Nexus Humans 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) 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 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) 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 This course is best suited to developers, engineers, and architects who want to use use Hadoop and related tools to solve real-world problems. Overview Skills learned in this course include:Creating a data set with Kite SDKDeveloping custom Flume components for data ingestionManaging a multi-stage workflow with OozieAnalyzing data with CrunchWriting user-defined functions for Hive and ImpalaWriting user-defined functions for Hive and ImpalaIndexing data with Cloudera Search Cloudera University?s four-day course for designing and building Big Data applications prepares you to analyze and solve real-world problems using Apache Hadoop and associated tools in the enterprise data hub (EDH). IntroductionApplication Architecture Scenario Explanation Understanding the Development Environment Identifying and Collecting Input Data Selecting Tools for Data Processing and Analysis Presenting Results to the Use Defining & Using Datasets Metadata Management What is Apache Avro? Avro Schemas Avro Schema Evolution Selecting a File Format Performance Considerations Using the Kite SDK Data Module What is the Kite SDK? Fundamental Data Module Concepts Creating New Data Sets Using the Kite SDK Loading, Accessing, and Deleting a Data Set Importing Relational Data with Apache Sqoop What is Apache Sqoop? Basic Imports Limiting Results Improving Sqoop?s Performance Sqoop 2 Capturing Data with Apache Flume What is Apache Flume? Basic Flume Architecture Flume Sources Flume Sinks Flume Configuration Logging Application Events to Hadoop Developing Custom Flume Components Flume Data Flow and Common Extension Points Custom Flume Sources Developing a Flume Pollable Source Developing a Flume Event-Driven Source Custom Flume Interceptors Developing a Header-Modifying Flume Interceptor Developing a Filtering Flume Interceptor Writing Avro Objects with a Custom Flume Interceptor Managing Workflows with Apache Oozie The Need for Workflow Management What is Apache Oozie? Defining an Oozie Workflow Validation, Packaging, and Deployment Running and Tracking Workflows Using the CLI Hue UI for Oozie Processing Data Pipelines with Apache Crunch What is Apache Crunch? Understanding the Crunch Pipeline Comparing Crunch to Java MapReduce Working with Crunch Projects Reading and Writing Data in Crunch Data Collection API Functions Utility Classes in the Crunch API Working with Tables in Apache Hive What is Apache Hive? Accessing Hive Basic Query Syntax Creating and Populating Hive Tables How Hive Reads Data Using the RegexSerDe in Hive Developing User-Defined Functions What are User-Defined Functions? Implementing a User-Defined Function Deploying Custom Libraries in Hive Registering a User-Defined Function in Hive Executing Interactive Queries with Impala What is Impala? Comparing Hive to Impala Running Queries in Impala Support for User-Defined Functions Data and Metadata Management Understanding Cloudera Search What is Cloudera Search? Search Architecture Supported Document Formats Indexing Data with Cloudera Search Collection and Schema Management Morphlines Indexing Data in Batch Mode Indexing Data in Near Real Time Presenting Results to Users Solr Query Syntax Building a Search UI with Hue Accessing Impala through JDBC Powering a Custom Web Application with Impala and Search

Advance your career in Criminal Justice! Master legal systems, study criminology, develop critical thinking skills, and contribute to a just society. Enrol for professional growth!

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Duration 1 Days 6 CPD hours This course is intended for This class is intended for the following: Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform. Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports. Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists. Overview This course teaches students the following skills:Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.Employ BigQuery and Cloud Datalab to carry out interactive data analysis.Train and use a neural network using TensorFlow.Employ ML APIs.Choose between different data processing products on the Google Cloud Platform. This course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. Introducing Google Cloud Platform Google Platform Fundamentals Overview. Google Cloud Platform Big Data Products. Compute and Storage Fundamentals CPUs on demand (Compute Engine). A global filesystem (Cloud Storage). CloudShell. Lab: Set up a Ingest-Transform-Publish data processing pipeline. Data Analytics on the Cloud Stepping-stones to the cloud. Cloud SQL: your SQL database on the cloud. Lab: Importing data into CloudSQL and running queries. Spark on Dataproc. Lab: Machine Learning Recommendations with Spark on Dataproc. Scaling Data Analysis Fast random access. Datalab. BigQuery. Lab: Build machine learning dataset. Machine Learning Machine Learning with TensorFlow. Lab: Carry out ML with TensorFlow Pre-built models for common needs. Lab: Employ ML APIs. Data Processing Architectures Message-oriented architectures with Pub/Sub. Creating pipelines with Dataflow. Reference architecture for real-time and batch data processing. Summary Why GCP? Where to go from here Additional Resources Additional course details: Nexus Humans Google Cloud Platform Big Data and Machine Learning Fundamentals 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 Google Cloud Platform Big Data and Machine Learning Fundamentals 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.