2455 Courses in Nottingham delivered Online

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

Take your sales people from average to high performance. Motivate and develop experienced sales professionals with some new insights and learning. Applying NLP principles, techniques and models, this workshop will introduce the core attitudes and behaviours that differentiate the excellent sales person from the average one. The programme will help participants: Understand and adopt the mindset and beliefs needed for sales excellence Build rapport and connect with buyers at a deeper and more personal level Recognise some of the thinking and language patterns that make each individual unique Ask powerful questions to further understand the unique world of the individual and how they make decisions Apply tools and techniques to empathise with clients - seeing things from their perspectives Tailor their sales approach to the individual buyer's style, and talk in their language Influence with integrity and sell to organisations and individuals successfully 1 Introduction Aims and objectives of the programme Personal introductions and objectives Workshop overview 2 An introduction to NLP and sales excellence with NLP An overview of NLP and applying it to selling The pillars of NLP The NLP model of communication The difference that makes the difference 3 Building enhanced rapport Defining rapport and why it is important when selling Going beyond the initial small talk Building relationships with individual decision-makers Matching and mirroring Levels of rapport 4 Understanding the buyer's personal buying map How we take in, filter and process information How we judge others based on our own experiences of the world The different ways in which we communicate when selling Recognising and understanding the language and thinking patterns of others Adapting your sales communication style to different buyers 5 Making sense of the buying process How we filter information through our senses Understanding how we see, hear and experience the world Visual, auditory and kinaesthetic buyers Listening for key insights What different buyers want from you to help them to buy Applying sensory awareness to the sales process 6 Successful sales mindset The connection between thoughts and actions The sales beliefs of excellence Identifying negative thoughts and beliefs that are holding you back How to change your mindset Adopting the sales beliefs of excellence 7 Powerful questions Reviewing and honing your questioning skills Understanding the questions that great sales people ask Avoiding assumptions Clean language questions Getting to the bottom of it - precision questions Turbo-charging how you qualify 8 Influencing with integrity Understanding empathy Stepping into the buyer's shoes Speaking the buyer's language Tailoring your sales approach to the individual Match, pace, lead - how to take your buyer with you 9 Putting it all together Personal learning summary and action plans

This course is your guide to deep learning in Python with Keras. You will discover the Keras Python library for deep learning and learn how to use it to develop and evaluate deep learning models.

4-Hour Discovery Day - NLP Training Near Me | Ely Wellbeing Neuro Linguistic Programming (NLP) is a collection of models and techniques that provide insights into human psychological processes. Through its various models, strategies and tools, NLP helps people to change their lives by taking control of their thoughts, feelings and behaviours. Our 4 Hour Discovery Day gives you an opportunity to learn the basics of Neuro Linguistic Programming; how it

Become a vulnerability assessment professional with the Nessus scanner for networks and learn to analyze and rank vulnerabilities, both manually and through automation. Explore vulnerability scanning with Metasploit and write custom professional reports. Learn to import results of Nmap in Nessus and create VA Project Worksheets to analyze vulnerability assessments.

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Want to become a full-stack software engineer who builds robust applications and seamless web experiences? The Software Engineering: Coding & Web Development Mini Bundle is your all-in-one toolkit for today’s software development industry, covering Python, Go Lang, UX, DevOps, and Javascript—skills in high demand across startups, tech giants, and digital agencies. Companies are hiring now, seeking candidates fluent in both backend and frontend technologies, as well as infrastructure and user experience. Equip yourself with this bundle and become the candidate they can’t ignore. Description This bundle is the perfect blend of backend and frontend skills with the operational edge needed for modern development. Learn Python and Go Lang for powerful backend programming, master Javascript to build engaging user interfaces, refine your projects with UX best practices, and optimize deployment pipelines through DevOps. Hiring managers want software engineers who understand every stage of the software lifecycle—from coding to deployment and user experience. Your fluency in Python, Go Lang, UX, DevOps, and Javascript demonstrates you are that versatile engineer. With competition growing fiercer daily, this bundle positions you to meet industry needs across web development, SaaS, cloud computing, and beyond. FAQ Who should take this bundle? Aspiring software engineers, full-stack developers, web developers, and devops engineers. If you want to master Python, Go Lang, UX, DevOps, and Javascript, this bundle is designed for you. How does this bundle improve my chances in web development? Because it covers both frontend (Javascript, UX) and backend (Python, Go Lang), plus deployment and maintenance (DevOps), giving you full lifecycle skills employers demand. Is this suitable for beginners? Yes! Whether you’re new or upgrading skills, the bundle builds you up to job readiness with real-world applications of these five core skills.

Algebra doesn’t have to be intimidating — in fact, with the right guidance, it can even feel satisfying. Our Algebra Fundamentals Course brings clarity to confusion and simplifies the language of maths in a way that makes sense, whether you're brushing up or learning from scratch. From equations and expressions to inequalities and graphs, this course lays the groundwork with a clear and steady rhythm that keeps numbers from dancing out of reach. Designed for learners of all backgrounds, this course takes a sensible and structured approach. It keeps things moving at a steady pace without jumping ahead or losing focus. Whether you're preparing for further studies or simply looking to sharpen your problem-solving instincts, you'll find each module refreshingly straightforward. There's no jargon parade — just solid algebra with a clear purpose. Let formulas feel less like a foreign language and more like familiar territory. Learning Outcomes: Apply algebraic concepts in real-world scenarios. Perform operations on algebraic expressions and solve linear equations. Work with quadratic polynomials and quadratic equations. Plot points and line graphs on a coordinate axis. Understand and work with algebraic fractions. Solve systems of simultaneous linear equations in two variables The Algebra Fundamentals course is an excellent opportunity for students to develop their algebraic skills and gain a deep understanding of fundamental concepts. By taking this course, you will learn how to perform operations on algebraic expressions and solve linear equations, quadratic polynomials, and systems of simultaneous linear equations in two variables. You will also develop your ability to plot points and line graphs on a coordinate axis and work with algebraic fractions. This course is ideal for students who want to pursue careers in engineering, science, economics, or any other field that requires a strong foundation in algebraic concepts. By taking this course, you will gain the necessary knowledge and skills to succeed in these fields and excel in your future academic and professional pursuits. With engaging lessons and real-world applications, this course is perfect for students of all backgrounds and skill levels. How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 15 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The course is ideal for highly motivated individuals or teams who want to enhance their professional skills and efficiently skilled employees. Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path The Algebra Fundamentals course provides you with the ability to explore different job opportunities across various industries with positions and pay scales such as upon completion of the course: Financial Analyst - £35,000-£65,000 Data Analyst - £25,000-£45,000 Market Research Analyst - £20,000-£40,000 Mechanical Engineer - £26,000-£50,000 Economist - £30,000-£70,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Overview Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home! Kickstart your career & boost your employability by helping you discover your skills, talents, and interests with our special Basic Arduino Crash Course Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides the professional training that employers are looking for in today's workplaces. The Basic Arduino Crash Course Course is one of the most prestigious training offered at Skillwise and is highly valued by employers for good reason. This Basic Arduino Crash Course Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Basic Arduino Crash Course Course, like every one of Study Hub's courses, is meticulously developed and well-researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly. At Skillwise, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from Skillwise, you get unlimited Lifetime access with 24/7 dedicated tutor support. Why buy this Basic Arduino Crash Course? Lifetime access to the course forever Digital Certificate, Transcript, and student ID are all included in the price Absolutely no hidden fees Directly receive CPD QS-accredited qualifications after course completion Receive one-to-one assistance every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Basic Arduino Crash Course there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for free. Original Hard Copy certificates need to be ordered at an additional cost of £8. Who is this course for? This Basic Arduino Crash Course course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skills. Prerequisites This Basic Arduino Crash Course does not require you to have any prior qualifications or experience. You can just enroll and start learning. This Basic Arduino Crash Course was made by professionals and it is compatible with all PCs, Macs, 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. Career path As this course comes with multiple courses included as a bonus, you will be able to pursue multiple occupations. This Basic Arduino Crash Course is a great way for you to gain multiple skills from the comfort of your home. Section 1: Introduction & Requirements Unit 1: Introduction 00:01:00 Unit 2: Instructor's Introduction 00:05:00 Unit 3: What is Arduino 00:02:00 Section 2: Objective to Remember Unit 1: The Holes in Board 00:01:00 Unit 2: Working Procedure 00:01:00 Unit 3: The Breadboard 00:05:00 Section 3: Thinking Process of Arduino Unit 1: Thinking Process of Arduino 00:06:00 Section 4: Making a Circuit Unit 1: Putting Together a Circuit 00:04:00 Section 5: Coding Arduino Unit 1: Cut and Paste Coding 00:12:00 Section 6: More About Circuit Diagram Unit 1: Circuit Diagram 00:03:00 Section 7: Practical Work Unit 1: Inputs: Buttons 00:04:00 Unit 2: Analog Input: IR sensor 00:04:00 Unit 3: Analog Input: Potentiometer 00:09:00 Assignment Assignment - Basic Arduino Crash Course

Data Analysis (Beginner): Data Analysis Course Online Are you trying to get the knowledge and abilities required to excel in data analysis at the beginner level? Our Data Analysis Course (Beginner) could be your perfect option for this. The Data Analysis Course (Beginner) offers comprehensive training in data analysis methodologies and tools. The Data Analysis Course (Beginner) covers topics such as data cleaning, visualisation, and statistical analysis. Also, the Data Analysis Course (Beginner) teaches programming in Python or R. Moreover, the Data Analysis Course (Beginner) equips students with essential skills for deriving insights from data. This Data Analysis Course (Beginner) explains data manipulation and interpretation. Enrol in our Data Analysis Course (Beginner) to prepare them for careers in data analysis across various industries. Main Course: Data Analytics Course (Beginner) [ Note: Free PDF certificate as soon as completing the Data Analysis (Beginner): Data Analysis Course] Data Analysis (Beginner): Data Analysis Course This Data Analysis (Beginner): Data Analysis Training Course consists of 12 modules. Who is this course for? Data Analysis (Beginner): Data Analysis Course This Data Analysis (Beginner): Data Analysis Course is recommended for anyone looking to advance in their data analysis career. Requirements Data Analysis (Beginner): Data Analysis Course To enrol in this Data Analysis (Beginner): Data Analysis Course, students must fulfil the following requirements: Data Analysis: Good Command over English language is mandatory to enrol in our Data Analysis Course. Data Analysis: Be energetic and self-motivated to complete our Data Analysis Course. Data Analysis: Basic computer Skill is required to complete our Data Analysis Course. Data Analysis: If you want to enrol in our Data Analysis Course, you must be at least 15 years old. Career path Data Analysis (Beginner): Data Analysis Course The Data Analysis (Beginner): Data Analysis Course opens up a wide range of work prospects, especially in the UK labour market.