1339 Scientist courses

This Professional Certificate Course in Advanced Analytics and Emerging Trends offers a comprehensive overview of advanced analytics tools, future-ready digital analytics, data mining, customer journey mapping, and the creation of customer-centric marketing campaigns. Participants will also learn how to stay current with emerging trends and adapt to evolving technologies in the dynamic field of digital marketing. After the successful completion of the course, you will be able to learn about the following: Advanced analytics techniques and tools Preparing for the future of digital analytics and marketing Concept of data mining and customer journey mapping and be able to create customer-centric marketing campaigns. How to stay up-to-date with emerging trends and technologies in digital marketing and be able to adapt to changes in the industry.   This Professional Certificate Course in Advanced Analytics and Emerging Trends provides a thorough grasp of advanced analytics tools. Participants will explore the future of digital analytics, understand data mining, and master customer journey mapping for creating customer-centric marketing campaigns. The course also focuses on staying current with emerging trends and technologies in digital marketing, fostering adaptability to industry changes. This Professional Certificate Course in Advanced Analytics and Emerging Trends provides expertise in advanced analytics tools. Participants will explore data mining, customer journey mapping, and create customer-centric marketing campaigns. The course ensures readiness for the future of digital analytics, emphasizing staying current with emerging trends and adapting to industry changes. 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. Advanced Analytics and Emerging Trends Self-paced pre-recorded learning content on this topic. Advanced Analytics And Emerging Trends 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, Professionals Navigating Emerging Trends Individuals in Customer Relationship Management Those Adapting to Industry Changes Data Analysts and Scientists Marketing Professionals Seeking Advanced Analytics Skills Digital Marketing Strategists Business Intelligence Professionals Marketing Managers Marketing Enthusiasts Seeking Future-Ready Knowledge 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.

This course unveils the crucial synergy between strategy and risk, emphasizing their paramount importance in organizational development. Delve into the strategic plan reviewing process, explore diverse types of strategic analysis, and gain proficiency in using tools for informed decision-making. Equip yourself with the skills to conduct Value Chain Analysis and competitive analysis, fostering a deep understanding of market dynamics. This course is a comprehensive exploration of risk analysis standard tools and models. It covers the strategic plan reviewing process, various types of strategic analysis, and the application of tools in strategic formulation. Participants will navigate the step-by-step process of Value Chain Analysis, gaining insights into competitive advantages. Additionally, the course highlights the benefits of competitive analysis for making informed business decisions. After the successful completion of this course, you will be able: ⦁ Understand the importance of reviewing strategy and risk. ⦁ Demonstrate knowledge of the strategic plan reviewing process and its role in organizational development. ⦁ Identify the different types of strategic analysis and their applications in formulating business strategies. ⦁ Describe the various tools used in strategic analysis. ⦁ Comprehend the step-by-step process of conducting Value Chain Analysis to assess a company's competitive advantage. ⦁ Recognize the benefits of competitive analysis in understanding market dynamics and making informed business decisions. Dive into the realm of risk analysis with precision through our specialized course. Explore industry-standard tools and models meticulously designed to sharpen your ability in evaluating and managing risks effectively. This hands-on program equips you with the expertise needed to employ both quantitative and qualitative analysis methods. Elevate your strategic decision-making by mastering these essential risk analysis frameworks, ensuring you become an invaluable asset in navigating complexities within any professional landscape. 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. Risk Analysis Standards, Tools and Models - Part 1 Self-paced pre-recorded learning content on this topic. Risk Analysis Standard Tools And Models 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.  1. Risk Analysts 2. Financial Planners 3. Project Managers 4. Compliance Officers 5. Data Scientists 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 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

Throughout this course, you will learn how to operate and maintain laboratory equipment and perform laboratory technician tasks.

Unleash the power of Artificial Intelligence in your business leadership. Discover how AI reshapes business models, explore the potential of Generative AI, and build a robust, future-ready AI strategy with our expert-led course.

Duration 2 Days 12 CPD hours This course is intended for This introductory-level course is intended for Business Analysts and Data Analysts (or anyone else in the data science realm) who are already comfortable working with numerical data in Excel or other spreadsheet environments. No prior programming experience is required, and a browser is the only tool necessary for the course. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Throughout the hands-on course students, will learn to leverage Python scripting for data science (to a basic level) using the most current and efficient skills and techniques. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore (to a basic level): How to work with Python interactively in web notebooks The essentials of Python scripting Key concepts necessary to enter the world of Data Science via Python This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it?s often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. An Overview of Python Why Python? Python in the Shell Python in Web Notebooks (iPython, Jupyter, Zeppelin) Demo: Python, Notebooks, and Data Science Getting Started Using variables Builtin functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Sequences, Arrays, Dictionaries and Sets About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Generator Expressions Nested sequences Working with Dictionaries Working with Sets Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Functions Defining functions Parameters Global and local scope Nested functions Returning values Essential Demos Sorting Exceptions Importing Modules Classes Regular Expressions The standard library Math functions The string module Dates and times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Python and Data Science Data Science Essentials Pandas Overview NumPy Overview SciKit Overview MatPlotLib Overview Working with Python in Data Science Additional course details: Nexus Humans Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 3 Days 18 CPD hours This course is intended for Data Wrangling with Python takes a practical approach to equip beginners with the most essential data analysis tools in the shortest possible time. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context. Overview By the end of this course, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently. In this course you will start with the absolute basics of Python, focusing mainly on data structures. Then you will delve into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python.This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The course will further help you grasp concepts through real-world examples and datasets. Introduction to Data Structure using Python Python for Data Wrangling Lists, Sets, Strings, Tuples, and Dictionaries Advanced Operations on Built-In Data Structure Advanced Data Structures Basic File Operations in Python Introduction to NumPy, Pandas, and Matplotlib NumPy Arrays Pandas DataFrames Statistics and Visualization with NumPy and Pandas Using NumPy and Pandas to Calculate Basic Descriptive Statistics on the DataFrame Deep Dive into Data Wrangling with Python Subsetting, Filtering, and Grouping Detecting Outliers and Handling Missing Values Concatenating, Merging, and Joining Useful Methods of Pandas Get Comfortable with a Different Kind of Data Sources Reading Data from Different Text-Based (and Non-Text-Based) Sources Introduction to BeautifulSoup4 and Web Page Parsing Learning the Hidden Secrets of Data Wrangling Advanced List Comprehension and the zip Function Data Formatting Advanced Web Scraping and Data Gathering Basics of Web Scraping and BeautifulSoup libraries Reading Data from XML RDBMS and SQL Refresher of RDBMS and SQL Using an RDBMS (MySQL/PostgreSQL/SQLite) Application in real life and Conclusion of course Applying Your Knowledge to a Real-life Data Wrangling Task An Extension to Data Wrangling

Duration 5 Days 30 CPD hours This course is intended for This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming. However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other data-driven situations. Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business. Overview In this course, you will learn to: Use data science principles to address business issues. Apply the extract, transform, and load (ETL) process to prepare datasets. Use multiple techniques to analyze data and extract valuable insights. Design a machine learning approach to address business issues. Train, tune, and evaluate classification models. Train, tune, and evaluate regression and forecasting models. Train, tune, and evaluate clustering models. Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance. For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, it can also inform?by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice Addressing Business Issues with Data Science Topic A: Initiate a Data Science Project Topic B: Formulate a Data Science Problem Extracting, Transforming, and Loading Data Topic A: Extract Data Topic B: Transform Data Topic C: Load Data Analyzing Data Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Use Visualizations to Analyze Data Topic D: Preprocess Data Designing a Machine Learning Approach Topic A: Identify Machine Learning Concepts Topic B: Test a Hypothesis Developing Classification Models Topic A: Train and Tune Classification Models Topic B: Evaluate Classification Models Developing Regression Models Topic A: Train and Tune Regression Models Topic B: Evaluate Regression Models Developing Clustering Models Topic A: Train and Tune Clustering Models Topic B: Evaluate Clustering Models Finalizing a Data Science Project Topic A: Communicate Results to Stakeholders Topic B: Demonstrate Models in a Web App Topic C: Implement and Test Production Pipelines

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: A technical audience at an intermediate level Overview Using Amazon SageMaker, this course teaches you how to: Prepare a dataset for training. Train and evaluate a machine learning model. Automatically tune a machine learning model. Prepare a machine learning model for production. Think critically about machine learning model results In this course, learn how to solve a real-world use case with machine learning and produce actionable results using Amazon SageMaker. This course teaches you how to use Amazon SageMaker to cover the different stages of the typical data science process, from analyzing and visualizing a data set, to preparing the data and feature engineering, down to the practical aspects of model building, training, tuning and deployment. Day 1 Business problem: Churn prediction Load and display the dataset Assess features and determine which Amazon SageMaker algorithm to use Use Amazon Sagemaker to train, evaluate, and automatically tune the model Deploy the model Assess relative cost of errors Additional course details: Nexus Humans Practical Data Science with Amazon SageMaker 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 Practical Data Science with Amazon SageMaker 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.

Highlights of the Course Course Type: Online Learning Duration: 1 to 2 hours Tutor Support: Tutor support is included Customer Support: 24/7 customer support is available Quality Training: The course is designed by an industry expert Recognised Credential: Recognised and Valuable Certification Completion Certificate: Free Course Completion Certificate Included Instalment: 3 Installment Plan on checkout What you will learn from this course? Gain comprehensive knowledge about NLP Understand the core competencies and principles of NLP Explore the various areas of NLP Know how to apply the skills you acquired from this course in a real-life context Become a confident and expert NLP practitioner NLP Practitioner Certification - Internationally Accredited Master the skills you need to propel your career forward in NLP. This course will equip you with the essential knowledge and skillset that will make you a confident NLP practitioner and take your career to the next level. This comprehensive NLP practitioner certification course is designed to help you surpass your professional goals. The skills and knowledge that you will gain through studying this NLP practitioner certification course will help you get one step closer to your professional aspirations and develop your skills for a rewarding career. This comprehensive course will teach you the theory of effective NLP practice and equip you with the essential skills, confidence and competence to assist you in the NLP industry. You'll gain a solid understanding of the core competencies required to drive a successful career in NLP. This course is designed by industry experts, so you'll gain knowledge and skills based on the latest expertise and best practices. This extensive course is designed for NLP practitioner or for people who are aspiring to specialise in NLP. Enrol in this NLP practitioner certification course today and take the next step towards your personal and professional goals. Earn industry-recognised credentials to demonstrate your new skills and add extra value to your CV that will help you outshine other candidates. Who is this Course for? This comprehensive NLP practitioner certification course is ideal for anyone wishing to boost their career profile or advance their career in this field by gaining a thorough understanding of the subject. Anyone willing to gain extensive knowledge on this NLP can also take this course. Whether you are a complete beginner or an aspiring professional, this course will provide you with the necessary skills and professional competence, and open your doors to a wide number of professions within your chosen sector. Entry Requirements This NLP practitioner certification course has no academic prerequisites and is open to students from all academic disciplines. You will, however, need a laptop, desktop, tablet, or smartphone, as well as a reliable internet connection. Assessment This NLP practitioner certification course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%. Advance Your Career This NLP practitioner certification course will provide you with a fresh opportunity to enter the relevant job market and choose your desired career path. Additionally, you will be able to advance your career, increase your level of competition in your chosen field, and highlight these skills on your resume. Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. Course Curriculum Supplementary Resources Supplementary Resources - NLP Practitioner Certification - Internationally Accredited 00:00:00 Basics of Neuro-Linguistic Programming (NLP) Programme Overview 00:02:00 Introduction to NLP 00:03:00 How Does NLP Work 00:03:00 Key Concepts in NLP Logical Levels of Change 00:08:00 Core Concepts of Neuro-Linguistic Programming 00:03:00 Understanding Mental Maps, Confirmation Bias, and Cognitive Dissonance 00:05:00 Mock Assessment Mock Assessment 00:10:00 Application of NLP Techniques Neuro-Linguistic Programming Planning 00:03:00 Techniques of Neuro-Linguistic Programming 00:02:00 Taking Charge of Your Life 00:02:00 Communication 00:02:00 Building Rapport 00:03:00 States and Anchors 00:03:00 Influence and Persuasion 00:02:00 Hypnotizing the Audience 00:03:00 Stories and Metaphors 00:03:00 Affirmations 00:02:00 Reframing 00:02:00 Meta Programs 00:03:00 Time and Timeline Therapy 00:02:00 Fast Phobia Cure 00:03:00 GROW Model 00:03:00 FUEL Model 00:03:00 CLEAR Model 00:04:00 OSCAR Model 00:03:00 Final Assessment Final Assessment 00:10:00 Obtain Your Certificate Order Your Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00