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Overview This comprehensive course on Data Science & Machine Learning with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science & Machine Learning with Python 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 Data Science & Machine Learning with Python. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with Python 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 2 sections • 90 lectures • 10:24:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:08:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:07:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00

LEARN HOW IRIDOLOGY CAN MAKE A HUGE CONTRIBUTION TO ANY COMPLEMENTARY PRACTICE A MESSAGE FROM THE AUTHOR I want to welcome you most warmly to the study of Iridology. Students of our course have taken their knowledge out into the world of practice and they have been able to see more penetratingly into the health of their patients. They have seen many truths about causes and effects in health and disease - that is what allows you to understand those extra things that make you into an even better healer. I think you are going to find this the most intriguing and absorbing study and, certainly, that is my sincere hope. As you precede, much of what you learn will amaze you and inspire wonder at the ways of the human body and mind. As you tread this very special road, I pass on to you the words that Bernard Jensen gave me years ago when I was his student, inscribed upon the inside cover of his book: “Seek the Higher Values in Life”. DR. LAWRENCE PLASKETT WHAT IS IRIDOLOGY? Iridology is the art of iris analysis. The iris is connected to the brain via the hypothalamus and can give naturopathic read outs on tissue conditions in various parts of the body. With training and practice it is possible to read signs indicative of biochemical, emotional and environmental influences that are hard to determine by other means. We can thus interpret health (and even aspects of personality) by close examination of the eyes, using suitable illumination and a magnifying glass. The close relationship between naturopathic iridology as an assessment tool and nutritional therapy and other naturopathic disciplines continues and grows closer. Now Iridology can make a huge contribution to complementary therapeutic practice and enhanced by our wonderful digital collection of eye photographs, the learning process with the Plaskett International College is a profound and exciting one. We teach Iridology quite separately from other topics and anyone who possesses, or expects to possess, a practitioner's qualification in any therapeutic discipline, may join the course. Course Duration 12 months Study Hours 200 hours Course Content 9 sections Course Fee £495 How Can Iridology Help Practitioners? Examples of how iridology can help practitioners Did you know that some iris features are so very plain that you can see them with the naked eye in ordinary social contact? You can see from two or three feet away in many cases that the person has a toxic digestive system (a strong wide dark ring around the pupil margin). You can often tell that the person has an overactive stomach (a narrow bright white ring very close to the pupil). You can tell when the skin is overlaid with toxins so that the skin's function in excreting toxins from the body is jeopardised (very narrow dark ring around the iris margin). You can tell in some people (rather advanced cases) that they suffer badly from sodium and potassium imbalance and have placed themselves at potential risk from cholesterol accumulation (the so-called corneal arcus, a white or off-white cloudy deposit, usually fairly thick, around the iris margin).  Another example is the ring of spots or 'tophi' represented by the lymphatic rosary. Its mere presence tells one that there is sluggishness in the lymphatic system. When these tophi are darkly pigmented, the situation gives rise to concern for the possible generation of lymphatic illness. Using the precise positioning of iris reflex areas contained on the iris chart, one may distinguish many key points of analysis. Areas of stress and tension can be pinpointed by identifying 'contraction furrows’. Past injuries and adhesions show themselves as contortions of the normally regular and even iris fibres. You can answer questions like:- Is it the pancreas or the liver that is responsible for the trouble? Is the patient's hypertension caused by a defect of or toxic deposits in the particular brain area that is geared to control blood pressure? One of Jensen's rather dramatic illustrations is of the iris of a man who has just been shot. It shows the precise areas of tissue damage within the body and the response is very fast. The number of potential examples is almost without limit. The above may suffice to show the types of things that iridology can do for practitioners. We hope it will help you decide to study Iridology with the Plaskett International College. Course Overview The course covers the nature of iris observation, the nutritive zone, the iris chart, the chronic and acute, the intestinal and stomach zones and nerve collarette, the constitution type, respiratory system, lacunae, open lacuna, inherent weaknesses, the organs of elimination, other organs, special signs, complete diagnosis of a subject. The treatment of the topic follows the principles of Bernard Jensen in the USA. Once the basics have been learnt, the course teachings then extend considerably by bringing in the work of Dorothy Hall and of Dr Josef Deck, both of which are the subject of a special presentation during the course. The published insights of Farida Sharan and Harri Wolf, while not separately presented, also influence the presentation of the course material. Both the Australian School, (Dorothy Hall) and the German School, (Dr Deck/Harri Wolf), offer an added dimension to the study and interpretation of the constitution. PERSONALITY ASPECTS & CONSTITUTIONAL TYPES The study focuses upon the different personality aspects, which show up in different constitutional types. Dorothy Hall gives insights into what contributes to various different types of personality and their emotional and mental responses and their pre-dispositions to health or disease. Different sorts of people can have different priorities, preferences and imperatives built into their very nature from or before birth, sometimes determining the course of their entire lives and their attitudes to the world and to other people. AN EMPATHY BETWEEN PATIENT & PRACTITIONER The course teaches an understanding of these types and facilitates an empathy between patient and practitioner. It shows how people of the differing constitutional types are likely to go out of balance either mentally or emotionally and how their vulnerability to various physical ailments varies. The German School offers a very exciting and precise approach to the constitutional types, which is really quite different, but no less helpful. It highlights variations in the susceptibility to diseases of different organs and systems. THE 3 SCHOOLS OF THOUGHT It is a prime purpose of this course, not only to teach these differing positions, but also to demonstrate how it is that all three of these major schools of Iridology embody different aspects of the truth, how each is individually valuable and how a full and deep understanding of the meaning of 'constitution' can be gained through a sympathetic synthesis of the contributions from all three of these schools. BREAKDOWN OF THE COURSE SECTIONS In total there are 9 sections comprising of text, videos and iris images to study: SECTION 1 GENERAL PRACTICE AND AN ACCOUNT OF THE NUTRITIVE ZONE Areas Covered Iris colour Information that iridology can give us The structure of the eye and the iris Using the iris as an assessment tool The principle of reflex areas The Nutritive Zone Abnormality in the colon The Collarette (autonomic nerve wreath or anw) Diagnosis of the constitution based upon fibre structure Studies on images of real eyes SECTION 2 FEATURES OF THE FIBRES OUTSIDE THE COLLARETTE Areas Covered The general layout of fibres outside the collarette Inherent weaknesses First stage in further deterioration of an inherent weakness The meaning of darkness in the iris The development of discrete – open lacunae Lacunae Further notes about lightness and darkness amongst the fibres Healing lines Crypts Round the iris chart – the left iris Round the iris chart – the right iris Checking which structures and inside and which outside the collarette The organ systems The neural arc reflex SECTION 3 SPECIAL SIGNS Areas covered The corneal arcus (sodium ring, cholesterol ring, lipemic ring) The tophi (also lymphatic tophi or lymphatic rosary) Corneal Arcus The anaemia sign The catarrhal sign Acidity Grey background Scurf rim Circulatory ring Sphincter muscle (also called pupillary sphincter) Pigments (topastible or topolabile) Psoric spots Contrcation furrows Radial furrows SECTION 4 THE CONSTITUTIONS IN RELATION TO PERSONALITY TYPE AND DISEASE DISPOSITION Areas covered Very resilient Resilient average Moderately resilient Mildly resilient SECTION 5 MORE ABOUT WHITE SIGNS Areas covered Revision of distinctions between the different white signs Pictures of irises with white signs, with commentaries Further interpretation of the corneal arcus Further interpretation of the lytophi More general interpretation of the colour white SECTION 6 COLOURS IN THE IRIS AND OTHER SPECIAL SIGNS Areas Covered Yellow pigment in the iris Orange pigment Brown pigment Contraction furrows Radial furrows Psoric spots Pupillary border The “friendly fibrils” sign Summary of remedies SECTION 7 THE CONSTITUTION AND SIGNS ACCORDING TO THE GERMAN SCHOOL Areas Covered The German school of iridology Our approach to teaching the German school Introduction to the German constitutional types The lymphatic constitutions Mixed biliary constitution or biliary constitution Haematogenic (or haematogenous) constitution The way to use information on the German constitutions New signs that are specific to the German school Treatment recommendations for constitutional types SECTION 8  ADVANCED STUDIES OF THE IRIS Areas Covered Further details of the iris chart – its layout and its implications Neural arc reflex Deformation of pupil shape and position Advanced study of fibre separations, sinuosity, injuries & adhesions Lacunae of different shape and appearance The b3 bulge and the pterygium Working with genetically brown eyes SECTION 9  THE CONSULTATION & THE PRACTICALITIES Areas Covered Diagnosing pathology of individual critical organs Personality interpretations based upon the German school Conducting an iridology consultation Practical aspects of iris examination Making drawings of the iris and recording the data The uses, advantages and limitations of iris photography and its place in iridology practice Equipments and techniques of iris photography Using the computer to store and process digital images The interaction of signs Interpreting the whole iris in conjunction with the case study Pointers to treatment Carrying out case histories TESTIMONIALS Here's what students have to say about the course Emma Rubio, Health Coach Spain "As a Health Coach I decided to pursue my studies with the Plaskett College to become a Nutritional Therapist. For that, I am also studying Iridology. I am happy to have a tutor to answer my doubts and I like the flexibility that the College offers me. I love the subject of Iridology and the way it is explained, I also like having some videos of Dr Plaskett teaching Iridology as I admire him." Dr Ezequiel Lafontaine, Iridologist Puerto Rico "I LOVE IRIDOLOGY. I have over 30 iridology books, Italian, French, German, Spanish and English, plus over 4,000 photos from my own practice. I took this course for a refresher course and found the material was second to none." Mrs D. Moothy, Nutritional Therapist Mauritius “The distance learning courses have given me the opportunity to pursue my dreams through a program that was not only flexible and convenient for my schedule, but was also challenging and rewarding. I thoroughly enjoyed the readings and the assignments but most importantly, I enjoyed being able to do things at my pace. I must say that the most exciting and challenging course was the Iridology Diploma, and I am happy that I was able to do well in all the courses."

This course is perfect for the beginner but also delves into building a SAS Model and intermediate topics. Learn SAS Data Step, SQL Step, Macros, SAS Model Building, Predictive Analytics, SAS and ML. If you are using SAS Enterprise Guide and want to learn how to code/program instead of using the point-and-click interface, this course is ideal!

Start your journey with the Linux command line with zero knowledge. This course will start from scratch with instructions to install a Linux OS on a virtual machine and advance to higher-level concepts with no prior knowledge required.

If you want to learn Java from not knowing anything to a paid Java Developer, then this is a course for you! Java is one of the most popular languages in the World. It's used by companies like Google, Accenture, Target, CenturyLink, Intel, Symantec, T-Mobile, eBay, Capital One, Groupon, New Relic, Nielsen, Uber, Spotify, Philips, Chegg, Yelp, Okta, Slack, Thomson Reuters, Opower, Zillow, Cloudera, Netflix, Canon, TripAdvisor and many more. This means the demand is not scarce. With Java Skills you will always have a job, and companies all over the world will be coming to you! This course is designed to teach you everything you need to know about Java in order to build high-end, efficient and scalable Java Applications. If you want to become: a highly paid Java Developer an expert Java Programmer companies want to hire a Freelancer Java Programmer who builds Enterprises Java Applications a person who can build their own business applications using Java Programming Language an Android Developer a Java Web/Enterprise Applications Developer better at Java ( sharpen your Java Knowledge and go deep into learning Advanced Java) a Certified Java Developer... ... much more... Then this course is for you and much more.... You'll be immersed into Java from the first lecture to the end. You will also receive a Certificate of Completion so you can present to your potential employer. Why this Course? Why is this the best Course To Learn Java? Well, if you are here is probably because you've either looked online for Java tutorials or maybe watched a lot of youtube videos and still can't really grasp core Java Programming Principles. You see, out there on the Internet, you can find a lot of information, but the problem is that everything is scattered around and very frustrating to actually learn the right way since all you get is fragments of information. This is where this Complete Java MasterClass shines - it takes you from nothing to actually building amazing Java Applications, and MOST importantly, you'll learn the Ins and Outs of Java Programming Language. With the knowledge you gain from this course you can build any Java Based Application - Web Applications, Android Mobile Apps, Desktop Applications and even program your DVD Player! Here's a list of some of the things you'll learn: Everything pertaining to Java - Java keywords, Java lingo (operators, if statements, for loops, switch statements, while loops) and many other basic, fundamentals that will help you have a solid Java knowledge. I will show you how to install all the tools you need in order to run Java programs such as IntelliJ ( which is the development tool used to code in Java ). Also, will show you how to install the Java libraries onto your machine (Windows, Linux and Mac). By the way, if you are using Eclipse, Jedit, Notepad, Netbeans or any other IDE, it's all good - you will still be learning a lot from this course. I will show you how to think like a Pro Programmer when learning Java, and how to use the Java knowledge and transfer it to build Android Apps , Web Apps (using many other Java Frameworks like Spring Framework, Hibernate and more) Java Object Oriented Programming so you can re-use code and write truly scalable and efficient code. You'll Learn JavaFX library and build amazing User Interfaces that will make your potential employers want to hire you right away! And so much more.... My goal in this course is to give you everything I know about Java so that you can be the best Java Programmer in the market! So that you become a Well-Rounded Java Programmer! All I teach you is what I wished I had known when I first started learning to Program in Java. Don't just take my word for it, see what my past students had to say about my courses and my teaching style: 'Very well thought-out course. Flows smoothly with great delivery. I have been developing Android Apps for several years and I still found this course to be informative, relevant, and helpful. I would recommend everyone take this course if you are new to Android or returning for a refresher course.' - Douglas Pillsbury 'Great course. very easy in understanding and friendly learning. Good Job Sir. Thanks for this.' - Muhammad Adnan 'I am very satisfied with this course. I have only attended the Android part because I had a basic knowledge on Java. I really like how Paulo teaches. He goes step by step and you can understand everything. My first language is not english, but he speaks very clearly, I can understand every word. Also, he is a happy guy, and you can hear that throug the courses that he really loves what he is doing. ' - Antal Bereczki 'This course is ideal for beginners. This guy is a good teacher. As i get deeper, i feel i am gaining more and more power...haha. I honestly think this is the best money i have ever spent in my life. This course is worth the money 100 times over. OMG, this good. Paulo, you are FANTASTIC !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!' - Sean 'So far one of the best courses and instructors i have experienced in Udemy.' - Jim Landon Are you afraid that maybe since you are an experience developer, and have never done Java before, you won't be able to learn Java? Take a look at what one of my students said about my course and teaching style: 'As a web developer I always thought that learning Android development will be hard. But with this course it's piece of cake!' - SaÅ¡a Lacković Students love my course so much that they can't even contain themselves... Look at what one student wrote: 'If there's something more than 5 starts, I would have given to this course. Really great content along with detailed explanation. Keep going on by updating and enhancing the content of this course. Personally, I enjoy every lecture I attend. PAULO... YOU ARE BEST OF THE BEST 🙂  Thanks a lot for this great course, Best regards.' - Bassel Nasief Sign up today, and look forward to: Over 30 hours of HD 1080p video content Source code Assignments Building several fully-fledged Java Applications All the knowledge you need to start building any Java Application you want - Web, Desktop and more. Thousands of dollars worth of design assets My best selling From Zero to a Pro Mobile Developer eBook It's proven that the best way to learn something is by immersing yourself in the subject you are trying to learn. If you want to master Java Programming, then you are in the right place. By the end of this course, you will master Java Programming no matter the level of experience you are at right now.  In this comprehensive course, you will be learning by doing, by coding alongside me. You'll understand exactly what I am doing and why. You will hone this Java Programming craft. Why learn Java compared to other programming languages? If you do a quick google search, you'll find that Java is the most popular Programming Language in use according to TIOBE index, since it's the ONLY language that works across all computer platform. Java has the capability to run into different devices ( Android included) without needing to be recompiled for each one. Hence, the slogan 'Write once, run anywhere' This is why Java is everywhere. Literally, everywhere! Can you see the potential of making a really good living by becoming a Java Developer? Give yourself the competitive advantage by learning the most popular programming language of all times - Java! If you know Java, you'll always be competitive in the market. You will be at the top of the food chain! REMEMBER... I'm so confident that you'll love this course that we're offering a FULL money back guarantee for 30 days! So it's a complete no-brainer, sign up today with ZERO risk and EVERYTHING to gain. So what are you waiting for? Click the Enroll Now button and join the world's most highly rated Java 9 Masterclass - Beginner to Expert. Who is the target audience? Anyone who wants to learn Java Programming Language Anyone who wants to learn JavaFX, Java Web Application Development, Java Databases What you'll learn Have a Full Java Programming Language Core Knowledge Build JavaFX User Interfaces and Applications Build Scalable, Maintainable and Clean Java Programs Learn how to Use Many Java Enterprise Frameworks like SpringBoot and Vaadin to Build Java Enterprise Applications Become a Well-Rounded Java Programmer - who can see the big picture of Applications to be built Requirements Have a Computer and know how to turn it on and off. Willingness and drive to learn, strong work ethics, a doer mentality You - show up ready to learn!

This course for beginners will help you build a solid foundation in programming with Python 3. We will cover core concepts such as Python statements, variables, data types, lists, typecasting, comments, conditional statements, loops, file handling, OOP concepts, and more. A carefully structured course with live demonstrations to get you started.

Embark on a transformative journey into the realm of programming with our Intermediate Python Coding course. Picture yourself delving deeper into the world of Python, a language known for its versatility and efficiency. This course begins with a refresher introduction, setting a solid foundation before advancing to more complex concepts. It's designed not just to teach but to immerse you in the intricacies of Python. From understanding the fundamentals of classes and methods to unraveling the complexities of Object-Oriented Programming (OOP), each section is a step towards mastering this powerful programming language. Whether you're looking to enhance your coding skills for professional growth or personal satisfaction, this course bridges the gap between basic understanding and advanced proficiency. As you progress, you'll explore the sophisticated elements of Python, including inheritance, polymorphism, encapsulation, and abstraction. These concepts are not just taught theoretically; you'll see them come to life through practical applications, especially in the creation of Python games. This hands-on approach ensures that you're not just learning concepts but also applying them in real-world scenarios. The course also delves into Python's extensive libraries as you learn about modules, packages, and data handling with Pandas. Completing the course with error and exception handling, you emerge not just as someone who can code but as a problem-solver who can navigate through challenges and create efficient, elegant solutions. Learning Outcomes Gain a deeper understanding of Python classes, methods, and OOP principles. Develop skills in implementing inheritance, polymorphism, encapsulation, and abstraction in Python. Create interactive Python games and applications to apply coding skills practically. Learn to manage and utilise Python modules, packages, and the Pandas library. Master error and exception handling in Python for robust coding. Why choose this Intermediate Python Coding course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Intermediate Python Coding course for? Programmers looking to advance from basic to intermediate Python skills. Computer science students seeking a deeper understanding of Python. Software developers aiming to enhance their proficiency in Python. Data analysts and scientists interested in leveraging Python's capabilities. Hobbyists and tech enthusiasts keen on developing Python applications. Career path Software Developer: £30,000 - £60,000 Data Analyst: £25,000 - £50,000 Python Developer: £28,000 - £55,000 Machine Learning Engineer: £32,000 - £70,000 Data Scientist: £35,000 - £75,000 Back-end Developer: £27,000 - £53,000 Prerequisites This Beginner to Intermediate Python Coding does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Beginner to Intermediate Python Coding was made by professionals and it is compatible with all PC's, Mac's, 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. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Section 01: Introduction Course Introduction 00:02:00 Course Curriculum 00:05:00 How to get Pre-requisites 00:02:00 Getting Started on Windows, Linux or Mac 00:01:00 How to ask Great Questions 00:02:00 Section 02: Class Introduction to Class 00:07:00 Create a Class 00:09:00 Calling a Class Object 00:08:00 Class Parameters - Objects 00:05:00 Access Modifiers(theory) 00:10:00 Summary 00:02:00 Section 03: Methods Introduction to methods 00:06:00 Create a method 00:07:00 Method with parameters 00:12:00 Method default parameter 00:06:00 Multiple parameters. 00:05:00 Method return keyword. 00:04:00 Method Overloading. 00:05:00 Summary 00:02:00 Section 04: OOPs Object-Oriented Programming Introduction to OOPs 00:05:00 Classes and Objects 00:08:00 Class Constructors 00:07:00 Assessment Test1 00:01:00 Solution for Assessment Test1 00:03:00 Summary 00:01:00 Section 05: Inheritance and Polymorphism Introduction 00:04:00 Inheritance 00:13:00 Getter and Setter Methods 00:12:00 Polymorphism 00:13:00 Assessment Test2 00:03:00 Solution for Assessment Test2 00:03:00 Summary 00:01:00 Section 06: Encapsulation and Abstraction Introduction 00:03:00 Access Modifiers (public, protected, private) 00:21:00 Encapsulation 00:07:00 Abstraction 00:07:00 Summary 00:02:00 Section 07: Python Games for Intermediate Introduction 00:01:00 Dice Game 00:06:00 Card and Deck Game Playing 00:07:00 Summary 00:01:00 Section 08: Modules and Packages Introduction 00:01:00 PIP command installations 00:12:00 Modules 00:12:00 Naming Module 00:03:00 Built-in Modules 00:03:00 Packages 00:08:00 List Packages 00:03:00 Summary 00:02:00 Section 09: Working Files with Pandas Introduction 00:02:00 Reading CSV files 00:11:00 Writing CSV files 00:04:00 Summary 00:01:00 Section 10: Error and ExceptionHandling Introduction 00:01:00 Errors - Types of Errors 00:08:00 Try - ExceptExceptions Handling 00:07:00 Creating User-Defined Message 00:05:00 Try-Except-FinallyBlocks 00:07:00 Summary 00:02:00

Overview of Data Science & Machine Learning with Python Join our Data Science & Machine Learning with Python course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Data Science & Machine Learning with Python course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Data Science & Machine Learning with Python course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This Data Science & Machine Learning with Python Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Science & Machine Learning with Python. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online - Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Data Science & Machine Learning with Python course, you can order your CPD Accredited Digital / PDF Certificate for £5.99.  Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Data Science & Machine Learning with Python is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand.  On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements You don't need any educational qualification or experience to enrol in the Data Science & Machine Learning with Python course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Data Science & Machine Learning with Python Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:04:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:06:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Data Science & Machine Learning with Python 00:00:00

The course helps you learn how to program with Python without any prior experience. The course also emphasizes learning the Django framework. You'll work on 4 major projects that will ensure that you have acquired and implemented your newly added skills to make Python-based websites with Django.

Duration 2 Days 12 CPD hours This course is intended for The audience for this course includes professionals who are new to Looker who are interested in leveraging Looker for data analysis, visualization, and reporting. The course is designed for individuals seeking to gain a comprehensive understanding of Looker's functionalities and apply these skills in their organizations to drive data-driven decision-making. Overview This course combines expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our expert facilitator, you'll explore and gain: Comprehensive understanding of Looker's platform: Gain a solid foundation in Looker's key features, functionality, and interface, enabling you to navigate and utilize the platform effectively for your data analysis and visualization needs. Mastery of LookML and data modeling: Develop proficiency in Looker's unique data modeling language, LookML, to create customized and efficient data models that cater to your organization's specific requirements. Expertise in creating insightful Explores: Learn to build, customize, and save Explores with dimensions, measures, filters, and calculated fields, empowering you to analyze your data and uncover valuable insights. Proficiency in dashboard design and sharing: Acquire the skills to design visually appealing and informative dashboards, share them with different user roles, and schedule exports to keep stakeholders informed and up-to-date. Enhanced content organization with folders and boards: Understand how to effectively use folders and boards to organize, manage, and discover content within Looker, making it easily accessible for you and your team. Optional: Advanced visualization techniques for impactful storytelling: Master advanced visualization techniques, including customizations with HTML, CSS, and JavaScript, and interactive visualizations using Looker's API, to create compelling data stories that resonate with your audience. Discover the power of data analytics and visualization with our hands-on, two-day introductory course Looker Bootcamp: Analyzing and Visualizing Data with Looker. Designed for professionals who want to unlock valuable insights from their data, this immersive training experience will guide you through Looker's cutting-edge features and provide you with the essential skills to create engaging, interactive, and insightful reports and dashboards. Our experienced trainers will take you on a journey from the fundamentals of Looker and its unique data modeling language, LookML, to advanced visualization techniques and content organization strategies, ensuring you leave the course equipped to make data-driven decisions with confidence. Throughout the course, you will have the opportunity to participate in practical exercises and workshops that will help you apply the concepts and techniques learned in real-world scenarios. You will explore the potential of Looker's Explores, dive into LookML's capabilities, and master the art of dashboard design and sharing. Learn how to organize and manage your content with folders and boards and harness the power of advanced visualization techniques to make your data come alive. Getting Started with Looker Overview of Looker and its key features Navigating the Looker interface Looker terminology and basic concepts Connecting to Data Sources Setting up and managing data connections Exploring database schemas Understanding LookML: Looker's data modeling language Creating and Customizing Explores Building and customizing Explores Adding dimensions, measures, and filters Creating calculated fields Saving and organizing Explores Data Visualization Creating visualizations using Looker's visualization library Customizing chart types, colors, and labels Displaying visualizations in dashboards Introduction to Looker's API for custom visualizations Advanced Explores and LookML LookML refresher and best practices Creating derived tables and data transformations Managing access controls and data permissions Organizing and Sharing Content with Folders and Boards Introduction to folders and boards in Looker Creating and managing folders for organizing content Setting up boards for easy content discovery Sharing folders and boards with different user roles and permissions Dashboard Design and Sharing Best practices for dashboard design Adding, arranging, and resizing visualizations Scheduling and exporting dashboard data Advanced Visualization Techniques Customizing visualizations with HTML, CSS, and JavaScript Creating interactive visualizations using Looker's API Integrating Looker visualizations with other tools Hands-on Workshop and Project Participants work on a guided project to apply the skills learned Trainer provides individual support and guidance Project Presentations, Q&A, and Training Wrap-up Additional course details: Nexus Humans Looker Bootcamp: Analyzing and Visualizing Data with Looker (TTDVLK02) 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 Looker Bootcamp: Analyzing and Visualizing Data with Looker (TTDVLK02) 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.