1336 Scientist courses

Feeling Stuck in Your Career? The Data Science with Python (30 in 1) CPD Accredited Courses! Bundle is Your Skill-Building Solution. This exceptional collection of 30 premium courses is designed to encourage growth and improve your career opportunities. Suited to meet different interests and goals, the Data Science with Python bundle provides an engaging learning experience, helping you learn skills across various disciplines. With Data Science with Python (30 in 1) CPD Accredited Courses! Bundle, you'll have a personalised journey that aligns with your career goals and interests. This comprehensive package helps you confidently tackle new challenges, whether entering a new field or enhancing your existing knowledge. The Data Science with Python bundle is your gateway to expanding your career options, increasing job demand, and enhancing your skill set. 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Bundle Comprises the Following CPD Accredited Courses:3 Course 01: Python Data Science Course 02: R Programming for Data Science Course 03: Quick Data Science Approach from Scratch Course 04: SQL for Data Science, Data Analytics and Data Visualization Course 05: Programming AutoCAD with SQL Server Database Using C# Course 06: Big Data Analytics with PySpark Power BI and MongoDB Course 07: Develop Big Data Pipelines with R & Sparklyr & Tableau Course 08: Develop Big Data Pipelines with R, Sparklyr & Power BI Course 09: Data Center Training Essentials: Power & Electrical Course 10: Building Big Data Pipelines with PySpark MongoDB and Bokeh Course 11: Clinical Data Management with SAS Programming Course 12: Certificate in Data Entry and Management Course 13: Business Intelligence and Data Mining Course 14: Set Menu Prices for your restaurant using data Course 15: Data Analysis In Excel Course 16: Data Protection Course 17: Learn Python, JavaScript, and Microsoft SQL for Data science Course 18: Spatial Data Visualisation and Machine Learning in Python Course 19: Python Intermediate Training Course 20: Complete Python Machine Learning & Data Science Fundamentals Course 21: Python Programming Bible | Networking, GUI, Email, XML, CGI Course 22: Deep Learning & Neural Networks Python - Keras Course 23: The Complete Python 3 Course: Beginner to Advanced! 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Whether you are starting your career, switching industries, or enhancing your professional skills, the Data Science with Python bundle offers the flexibility and convenience to learn at your own pace. Make the Data Science with Python package your trusted partner in your lifelong learning journey. CPD 300 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Data Science with Python (30 in 1) CPD Accredited Courses! is perfect for: Expand your knowledge and skillset for a fulfilling career with the Data Science with Python bundle. Become a more valuable professional by earning CPD certification and mastering in-demand skills with the Data Science with Python bundle. Discover your passion or explore new career options with the diverse learning opportunities in the Data Science with Python bundle. Learn on your schedule, in the comfort of your home - the Data Science with Python bundle offers ultimate flexibility for busy individuals. 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Course Overview Machine learning as a programming technique has shaped the future of technology. In this course, you will learn how to build intelligent handwriting recognition apps from scratch using Python and Core ML. The Machine Learning for Apps Level 4 course will teach you how to take advantage of machine learning to code like a pro and build incredible apps that can make predictions. Designed by industry experts, it covers best practices for managing projects, core concepts for creating your own ML model, building a convolutional neural network, and much more. On successful completion, you will be able to build an amazing handwriting recognition app and convolutional neural network from scratch, and have an in-depth understanding of the core ML basics. This course is ideal for those with a basic understanding of iOS development. This best selling Machine Learning for Apps Level 4 has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Machine Learning for Apps Level 4 is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The Machine Learning for Apps Level 4 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 Machine Learning for Apps Level 4 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 Machine Learning for Apps Level 4, 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 Machine Learning for Apps Level 4 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 Machine Learning for Apps Level 4 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.

3 QLS Endorsed Diploma | QLS Hard Copy Certificate Included | 10 CPD Courses | Lifetime Access | 24/7 Tutor Support

This module aims to develop knowledge from research activities to gain an understanding of international trade using Marketing , Social Media and how AI plays a role in International Marketing

Let's learn the basic concepts for developing chatbots with machine learning models. This compact course will help you learn to use the power of Python to evaluate your chatbot datasets based on conversational notes, online resources, and websites. Garner hands-on practice in text generation with Python for chatbot development.

Data-Informed Decision Making in Projects: On-Demand Project management professionals constantly need to make project decisions that could be decisive for the outcome of their projects but often do not have sufficient information available to confidently make decisions. As a result, projects are increasingly falling short of delivering on their promises, requiring, more than ever, a data-informed approach to decision-making in the area of project delivery and management. The rapid growth of data comes with various challenges though, which consequently needs consideration of various critical factors for a successful implementation of a data-informed decision-making process in organizations and projects. What You Will Learn At the end of this program, you will be able to: Describe and understand the relevant methods and techniques to identify, acquire, and analyze relevant data points for decision making in projects Articulate analytical questions to focus on the real problems Identify potential shortfalls and gaps in project decision-making and apply actions to mitigate them Introduction to Data-Informed Decision Making The different types of decisions in projects Data-informed decision-making framework Shortcomings with traditional decision-making models Understanding the value of data for project delivery Issues in project management and how data can help solve them The DIKW Pyramid (Data, information, knowledge, wisdom) Types of data in projects Applying Data Analytics Understanding Data Analytics Levels of Data Analytics Data-Informed vs. Data-Driven Challenges and How to Address Them Project data availability and collection Data quality Behavioral blockers and bias Skills and Techniques Data literacy and data fluency Communicating for informed decision-making Monitoring and evaluating project decisions Implementing Data-Informed Decision Making Decision-making strategy and governance Project data culture Continuously improving decision quality Future Outlook for Decision-Making in Projects Data and AI Digital Decisioning

Data-Informed Decision Making in Projects: On-Demand Project management professionals constantly need to make project decisions that could be decisive for the outcome of their projects but often do not have sufficient information available to confidently make decisions. As a result, projects are increasingly falling short of delivering on their promises, requiring, more than ever, a data-informed approach to decision-making in the area of project delivery and management. The rapid growth of data comes with various challenges though, which consequently needs consideration of various critical factors for a successful implementation of a data-informed decision-making process in organizations and projects. What You Will Learn At the end of this program, you will be able to: Describe and understand the relevant methods and techniques to identify, acquire, and analyze relevant data points for decision making in projects Articulate analytical questions to focus on the real problems Identify potential shortfalls and gaps in project decision-making and apply actions to mitigate them Introduction to Data-Informed Decision Making The different types of decisions in projects Data-informed decision-making framework Shortcomings with traditional decision-making models Understanding the value of data for project delivery Issues in project management and how data can help solve them The DIKW Pyramid (Data, information, knowledge, wisdom) Types of data in projects Applying Data Analytics Understanding Data Analytics Levels of Data Analytics Data-Informed vs. Data-Driven Challenges and How to Address Them Project data availability and collection Data quality Behavioral blockers and bias Skills and Techniques Data literacy and data fluency Communicating for informed decision-making Monitoring and evaluating project decisions Implementing Data-Informed Decision Making Decision-making strategy and governance Project data culture Continuously improving decision quality Future Outlook for Decision-Making in Projects Data and AI Digital Decisioning

This award introduces the critical concepts associated with AI and explores its relationship with the systems and processes that make up the digital ecosystem. It explores how AI can empower organisations to utilise Big Data through the use of Business Analysis and Machine Learning, and encourages candidates to consider a future vision of the world that is powered by AI.

This course is designed for beginners, although we will go deep gradually, and is a highly focused course designed to master your Python skills in probability and statistics, which covers the major part of machine learning or data science-related career opportunities.

This comprehensive course will help you learn how to use the power of Python to evaluate your deep learning-based recommender system data sets based on user ratings and choices with a practical approach to building a deep learning-based recommender system by adopting a retrieval-based approach based on a two-tower model.