Cyber Security is yet another 'Teacher's Choice' course from Teachers Training for a complete understanding of the fundamental topics. You are also entitled to exclusive tutor support and a professional CPD-accredited certificate in addition to the special discounted price for a limited time. Just like all our courses, this Cyber Security and its curriculum have also been designed by expert teachers so that teachers of tomorrow can learn from the best and equip themselves with all the necessary skills. Consisting of several modules, the course teaches you everything you need to succeed in this profession. The course can be studied part-time. You can become accredited within 6 hours studying at your own pace. Your qualification will be recognised and can be checked for validity on our dedicated website. Why Choose Teachers Training Some of our website features are: This is a dedicated website for teaching 24/7 tutor support Interactive Content Affordable price Courses accredited by the UK's top awarding bodies 100% online Flexible deadline Entry Requirements No formal entry requirements. You need to have: Passion for learning A good understanding of the English language Be motivated and hard-working Over the age of 16. Certification CPD Certification from The Teachers Training Successfully completing the MCQ exam of this course qualifies you for a CPD-accredited certificate from The Teachers Training. You will be eligible for both PDF copy and hard copy of the certificate to showcase your achievement however you wish. You can get your digital certificate (PDF) for £4.99 only Hard copy certificates are also available, and you can get one for only £10.99 You can get both PDF and Hard copy certificates for just £12.99! The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs. FUNDAMENTALS OF NETWORKING Network Topologies 00:06:00 History and Applications of Computer Networking 00:06:00 Protocols and Standards 00:04:00 Introduction to OSI Model 00:04:00 Layers of OSI Model 00:07:00 Introduction to TCP/IP Model 00:10:00 OSI Model vs TCP/IP Model 00:04:00 Addressing in Computer Networks 00:09:00 IP Address- IPv4 and IPv6 00:07:00 Classes of IP Address 00:10:00 PRACTICAL : HOW TO FIND OUT YOUR PC's IP ADDRESS 00:03:00 PRACTICAL : HOW TO FIND OUT YOUR PC'S MAC ADDRESS 00:05:00 The Internet Protocol (IP) 00:07:00 Address Resolution Protocol (ARP) 00:09:00 Dynamic Host Configuration Protocol (DHCP) 00:08:00 Internet Control Message Protocol (ICMP) 00:06:00 RIP and OSPF Protocols 00:06:00 PRACTICAL : HOW TO FIND OUT THE PATH OF DATA PACKETS USING TRACERT 00:03:00 What are Sockets? 00:05:00 File Transfer Protocol (FTP) 00:03:00 Hypertext Transfer Protocol (HTTP) 00:04:00 Domain Name System (DNS) 00:03:00 GETTING STARTED WITH CYBER SECURITY Definition of Computer Security 00:03:00 Interesting Facts about Cyber Security 00:05:00 History of Cyber Security 00:07:00 Scope and Career Insights in Cyber Security 00:08:00 LET'S BEGIN - THE FUNDAMENTALS OF CYBER SECURITY Introduction 00:01:00 Types of Computer Security 00:03:00 Key Terms in Cyber Security 00:07:00 The Elements of Information Security 00:06:00 Types of Attacks 00:10:00 Roles in Cyber Security : Part 1 00:08:00 Roles in Cyber Security : Part 2 00:06:00 DIVING DEEP INTO CYBER SECURITY Security Architect's View of Security 00:08:00 What is Vulnerability Assessment? 00:05:00 4 Phases of Vulnerability Assessment 00:09:00 Introduction to Cryptography 00:06:00 Symmetric Encryption 00:03:00 Asymmetric Encryption 00:04:00 Hashing 00:07:00 Security Organizations 00:05:00 Critical Thinking in Cyber Security 00:04:00 The Five Critical Thinking Skills 00:06:00 PRACTICAL : USING NSLOOKUP TOOL 00:03:00 TYPES OF ACTORS, ATTACKS, MALWARE AND RESOURCES Different types of Actors in Cyber Security 00:10:00 Types of Cyber Attacks 00:04:00 Hacking Organizations around the Globe 00:05:00 Security Services and Mechanisms 00:03:00 Introduction to Threats 00:03:00 What is a Malware? 00:07:00 Types of Trojans 00:06:00 Types of Virus 00:07:00 Have you ever heard about a Ransomware? 00:09:00 The Cyber Kill Chain 00:09:00 Introduction to Social Engineering 00:05:00 Types of Social Engineering 00:07:00 KEY SECURITY CONCEPTS Confidentiality - The Most Important Element of Security 00:04:00 Introduction to Incident Response Team 00:05:00 Phases of Incident Response 00:05:00 Laws in Cyber Security 00:05:00 What are Audits in Cyber Security 00:04:00 Internal Audit vs External Audit 00:04:00 The NIST Framework 00:03:00 The COBIT Framework 00:04:00 FIREWALLS AND ANTIVIRUS Intrusion Detection System 00:05:00 Introduction to Firewalls 00:05:00 What is DMZ? 00:04:00 Different types of Firewalls 00:09:00
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This course focuses on understanding all the basic theory and programming skills required as a data scientist, featuring 35+ practical case studies covering common business problems faced by them. This course seeks to fill all those gaps in knowledge that scare off beginners and simultaneously apply your knowledge of data science and deep learning to real-world business problems.
Are you interested in sharing knowledge with others and gaining insightful conclusions from data? This online Power BI course is your comprehensive and in-depth introduction to this powerful software if you've ever been curious about the fascinating, artistic field of data analysis and visualisation. Microsoft Power BI has the potential to be your most effective tool. It comes with all of the features found in MS Excel, as well as many more. Power BI has a wide range of features and functionalities. By obtaining this Power BI training, you'll learn to make the most of all of Microsoft Power BI's features and produce insightful tables, graphs, and reports. Along with this Power BI course, you also receive a number of additional practical and supplemental courses in a package that will assist you in becoming an expert in the field of business and IT. With the supplementary business management course, you will acquire the technical abilities and business knowledge needed to put your skills to use in the industry. Working with various platform data, algorithms, and data structures all are part of the job description of a data analyst. As the course includes Data Structure and Graph theory algorithm courses, this package will aid in your skill improvement as a data analyst. These courses in this bundle will advance your Power BI proficiency and allow you to perform more reasonable experimentation with this Power BI tool. Along with this Power BI course, you will get 10 premium courses, an original hardcopy, 11 PDF Certificates (Main Course + Additional Courses) Student ID card as gifts. 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Benefits you'll get choosing Apex Learning: Pay once and get lifetime access to 11 CPD courses Free e-Learning App for engaging reading materials & helpful assistance Certificates, student ID for the course included in a one-time fee Free up your time - don't waste time and money travelling for classes Accessible, informative modules of course designed by expert instructors Learn about course at your ease - anytime, from anywhere Study the course from your computer, tablet or mobile device CPD accredited course - improve the chance of gaining professional skills Curriculum: Course 01: Complete Microsoft Power BI 2021 Introduction Preparing our Project Data Transformation - The Query Editor Data Transformation - Advanced Creating a Data Model Data Visualization Power BI & Python Storytelling with Data DAX - The Essentials DAX - The CALCULATE function Power BI Service - Power BI Cloud Row-Level Security More data sources Next steps to improve & stay up to date How will I get my Certificate? After successfully completing the Power BI course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificate: Free (Previously it was £6*11 = £66) Hard Copy Certificate: Free (For The Title Course: Previously it was £10) PS The delivery charge inside the UK is £3.99, and the international students have to pay £9.99. CPD 115 CPD hours / points Accredited by CPD Quality Standards Who is this course for? There are no strict requirements, and any experienced computer user is expected to be able to finish the project. This bundle will also be beneficial for, Students from all academic disciplines Students interested in powerful data analysis techniques Anyone in business who wants to transform data into information Users of Excel who want to advance their reporting and analysis Requirements This Power BI course has been designed to be fully compatible with tablets and smartphones. Career path These different credentials will add value to your resume and give you access to a wide range of industries, including, but not limited to, Data analysis IT industry Business and management Freelance worker Entrepreneur Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course (Complete Microsoft Power BI) absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.
We have completed a training course to teach you everything you need to know about Microneedling. Microneedling, also known as skin needling or collagen induction therapy, leads the way in skin rejuvenation. Safely delivered, this treatment carries no risk or downtime to the client. It is a procedure whereby a device, such as a derma roller or an automated pen device, is passed across the skin's surface, creating superficial punctures that stimulate a healing response. We work with Dr Pen and Beautier needling pen and the Clinicare range as part of this course and cover appropriate products from this range. Skills and knowledge from this course will be transferable to other brands. Our Microneedling Training Course will provide you with everything you need to know about the history and the use of microneedling, as well as all the technical aspects of it: safety, indications, technique and post-treatment tips for a successful outcome. This course will primarily focus on the face, although we touch on the scalp & body benefits of this treatment. Learn how to safely, confidently and expertly deliver this treatment with our fully accredited microneedling training course Course prerequisites Minimum 18 years of age Good command of English Be able to learn independently A strong desire to build a career in aesthetics Previous skin and facial training are desirable; we suggest that learners new to the industry enrol on our facial and skincare course before enrolling on our ClinicCare skin peel course. Course structure The online study, virtual lecture and in-person practical training All courses are intimate with four learners in class 2-1 ratio. One day of on-site training Online learning includes: Anatomy and physiology of the skin and tissues Infection control Sharps and hazardous waste training History of skin needling Treatable skin conditions Contraindications Consultation Aftercare Introduction to automated Pen Device and Dermaroller Pre-study microneedling (health and safety) Onsite training day includes: Face-to-face practical training with 1 model per treatment area Clinical set up Live treatment demonstrations Frequently Asked Questions Where is the Cosmetic College The Cosmetic College is located at: 3 Locks Court, 429 Crofton Road, Orpington, BR6 8NL How can I book? We have a few options for you to book. You can book by selecting an available training date above here on our website, by contacting us through email at hello@cosmetic.college or by contacting us on 0333 015 5117. Is a deposit required to book? All enrolments are charged an administration fee which is non-refundable. When you enrol you can elect to pay a deposit of 10% plus the administration fee or pay the total training course in full. We have full details of the terms and conditions of training course enrolments here What is the course duration? 1 day + pre-study via our online learning platform.
Creating Your Organization's Business Agility Strategy Optimally, your organization's business strategy and business agility strategy are completely coupled together, one seamlessly supporting the other. Practically, what many organizations experience today is a tug-of-war between their business strategy and this thing called 'business agility.' Or, a lack of business agility strategy altogether, leaving the business strategy more susceptible, and even fragile, when unforeseen changes inevitably occur. We need a way to think about business agility, coupled with business strategy, so that we can live into the reality of harnessing change for good. This session will expose you to a recently published body of work, Domains of Business Agility, which serves as a model for creating business agility strategy. Think of it as a skeleton, or a thinking tool. Used this way, the model allows leaders to answer the question, 'How much business agility do we need in various parts of our organization as a seamless support to our overall business strategy?' In this session, Lyssa Adkins, author of Coaching Agile Teams and Agile/Leadership Coach, leads you through the key steps for creating such a business agility/business strategy. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs.
Creating Your Organization's Business Agility Strategy Optimally, your organization's business strategy and business agility strategy are completely coupled together, one seamlessly supporting the other. Practically, what many organizations experience today is a tug-of-war between their business strategy and this thing called 'business agility.' Or, a lack of business agility strategy altogether, leaving the business strategy more susceptible, and even fragile, when unforeseen changes inevitably occur. We need a way to think about business agility, coupled with business strategy, so that we can live into the reality of harnessing change for good. This session will expose you to a recently published body of work, Domains of Business Agility, which serves as a model for creating business agility strategy. Think of it as a skeleton, or a thinking tool. Used this way, the model allows leaders to answer the question, 'How much business agility do we need in various parts of our organization as a seamless support to our overall business strategy?' In this session, Lyssa Adkins, author of Coaching Agile Teams and Agile/Leadership Coach, leads you through the key steps for creating such a business agility/business strategy. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs.
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
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