19091 Courses

Join our Business Management Diploma 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 Business Management Diploma course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Business Management Diploma 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! You will Learn The Following Things: 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 Business Management Diploma. 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 Business Management Diploma 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. (Each) Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Business Management Diploma 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 There is no prerequisite to enrol in this course. You don't need any educational qualification or experience to enrol in the Business Management Diploma 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 Business Management Diploma 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 Module 01: Introduction to Business Management Introduction to Business Management 00:25:00 Module 02: Operations Management Operations Management 00:24:00 Module 03: Introduction to Business Analysis Introduction to Business Analysis 00:14:00 Module 04: Strategic Analysis and Product Scope Strategic Analysis and Product Scope 00:28:00 Module 05: Project Management Project Management 00:19:00 Module 06: Business Development and Succession Planning Business Development and Succession Planning 00:24:00 Module 07- Business Process Management Business Process Management 00:44:00 Module 08: Planning & Forecasting Operations Planning & Forecasting Operations 00:21:00 Module 09: Performance Management Performance Management 00:18:00 Module 10: Management of Cash and Credit Management of Cash and Credit 00:19:00 Module 11: Managing Risk and Recovery Managing Risk and Recovery 00:26:00 Module 12: Quality Management Quality Management 00:21:00 Module 13: Communication Skills Communication Skills 00:25:00 Module 14: Business Environment Business Environment 00:16:00 Module 15: Organisational Skills Organisational Skills 01:16:00 Module 16: Negotiation Techniques Negotiation Techniques 00:16:00 Module 17: Human Resource Management Human Resource Management 00:19:00 Module 18: Motivation and Counselling Motivation and Counselling 00:19:00 Module 19: Customer Service Customer Service 00:16:00 Module 20: Time Management Time Management 00:40:00 Module 21: Conflict Management Conflict Management 00:14:00 Assignment Assignment - Business Management 00:00:00

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Unlock the secrets of the world's forests with our comprehensive course on Forestry. Designed for aspiring forestry professionals, environmental enthusiasts, and anyone curious about sustainable land management, this course dives deep into the essentials of forestry practices and principles. Key Features: CPD Certified Free Certificate from Reed CIQ Approved Developed by Specialist Lifetime Access In this forestry course, learners will explore the diverse world of forests and their management. They'll gain insights into forest ecosystems, understanding how plants, animals, and environments interact. Discovering the crucial role of forest soil, they'll learn its composition and significance for healthy forests. Silviculture will teach them methods to cultivate and sustainably manage forests for various purposes. Forest mensuration will introduce techniques to measure and assess forest resources accurately. They'll delve into forest surveying, mastering the skills needed to map and analyze forest landscapes. Timber harvesting will be explored in depth, covering techniques for sustainable extraction and its impact on ecosystems. Finally, urban forestry will highlight the importance of trees in urban environments and strategies for their conservation and management. Through this course, learners will develop a comprehensive understanding of forestry practices essential for sustainable environmental stewardship. Course Curriculum Module 01: Introduction to Forestry Module 02: Forest Ecosystem Module 03: Forest Soil Module 04: Silviculture Module 05: Forest Mensuration Module 06: Forest Surveying Module 07: Timber Harvesting Part One Module 08: Timber Harvesting Part Two Module 09: Urban Forestry Learning Outcomes Understand the fundamentals of forestry and its ecological significance. Analyze forest ecosystems and their components for conservation purposes. Evaluate forest soil characteristics and their impact on tree growth. Apply principles of silviculture for sustainable forest management practices. Utilize forest mensuration techniques to measure tree growth and biomass. Implement forest surveying methods to assess land and plan management strategies. CPD 10 CPD hours / points Accredited by CPD Quality Standards Forestry: Surveying, Soil, Mensuration and Ecosystem 1:44:34 1: Module 01: Introduction to Forestry 12:33 2: Module 02: Forest Ecosystem 13:14 3: Module 03: Forest Soil 11:15 4: Module 04: Silviculture 13:03 5: Module 05: Forest Mensuration 11:59 6: Module 06: Forest Surveying 13:32 7: Module 07: Timber Harvesting Part One 09:24 8: Module 08: Timber Harvesting Part Two 07:04 9: Module 09: Urban Forestry 11:30 10: CPD Certificate - Free 01:00 Who is this course for? Professionals in environmental science and forestry management sectors. Students pursuing degrees in forestry or related environmental studies. Individuals interested in land management and conservation careers. Forestry technicians seeking to enhance their technical knowledge. Environmental consultants specializing in forest ecosystem assessments. Career path Forest Officer Ecologist Arboriculturist Land Management Consultant Wildlife Conservation Officer Forestry Technician Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

Unlock the secrets of the world's forests with our comprehensive course on Forestry. Designed for aspiring forestry professionals, environmental enthusiasts, and anyone curious about sustainable land management, this course dives deep into the essentials of forestry practices and principles. Key Features: CPD Certified Free Certificate from Reed CIQ Approved Developed by Specialist Lifetime Access In this forestry course, learners will explore the diverse world of forests and their management. They'll gain insights into forest ecosystems, understanding how plants, animals, and environments interact. Discovering the crucial role of forest soil, they'll learn its composition and significance for healthy forests. Silviculture will teach them methods to cultivate and sustainably manage forests for various purposes. Forest mensuration will introduce techniques to measure and assess forest resources accurately. They'll delve into forest surveying, mastering the skills needed to map and analyze forest landscapes. Timber harvesting will be explored in depth, covering techniques for sustainable extraction and its impact on ecosystems. Finally, urban forestry will highlight the importance of trees in urban environments and strategies for their conservation and management. Through this course, learners will develop a comprehensive understanding of forestry practices essential for sustainable environmental stewardship. Course Curriculum Module 01: Introduction to Forestry Module 02: Forest Ecosystem Module 03: Forest Soil Module 04: Silviculture Module 05: Forest Mensuration Module 06: Forest Surveying Module 07: Timber Harvesting Part One Module 08: Timber Harvesting Part Two Module 09: Urban Forestry Learning Outcomes Understand the fundamentals of forestry and its ecological significance. Analyze forest ecosystems and their components for conservation purposes. Evaluate forest soil characteristics and their impact on tree growth. Apply principles of silviculture for sustainable forest management practices. Utilize forest mensuration techniques to measure tree growth and biomass. Implement forest surveying methods to assess land and plan management strategies. CPD 10 CPD hours / points Accredited by CPD Quality Standards Forestry: Surveying, Soil, Mensuration and Ecosystem 1:44:34 1: Module 01: Introduction to Forestry 12:33 2: Module 02: Forest Ecosystem 13:14 3: Module 03: Forest Soil 11:15 4: Module 04: Silviculture 13:03 5: Module 05: Forest Mensuration 11:59 6: Module 06: Forest Surveying 13:32 7: Module 07: Timber Harvesting Part One 09:24 8: Module 08: Timber Harvesting Part Two 07:04 9: Module 09: Urban Forestry 11:30 10: CPD Certificate - Free 01:00 Who is this course for? Professionals in environmental science and forestry management sectors. Students pursuing degrees in forestry or related environmental studies. Individuals interested in land management and conservation careers. Forestry technicians seeking to enhance their technical knowledge. Environmental consultants specializing in forest ecosystem assessments. Career path Forest Officer Ecologist Arboriculturist Land Management Consultant Wildlife Conservation Officer Forestry Technician Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

Unlock the secrets of the world's forests with our comprehensive course on Forestry. Designed for aspiring forestry professionals, environmental enthusiasts, and anyone curious about sustainable land management, this course dives deep into the essentials of forestry practices and principles. Key Features: CPD Certified Free Certificate from Reed CIQ Approved Developed by Specialist Lifetime Access In this forestry course, learners will explore the diverse world of forests and their management. They'll gain insights into forest ecosystems, understanding how plants, animals, and environments interact. Discovering the crucial role of forest soil, they'll learn its composition and significance for healthy forests. Silviculture will teach them methods to cultivate and sustainably manage forests for various purposes. Forest mensuration will introduce techniques to measure and assess forest resources accurately. They'll delve into forest surveying, mastering the skills needed to map and analyze forest landscapes. Timber harvesting will be explored in depth, covering techniques for sustainable extraction and its impact on ecosystems. Finally, urban forestry will highlight the importance of trees in urban environments and strategies for their conservation and management. Through this course, learners will develop a comprehensive understanding of forestry practices essential for sustainable environmental stewardship. Course Curriculum Module 01: Introduction to Forestry Module 02: Forest Ecosystem Module 03: Forest Soil Module 04: Silviculture Module 05: Forest Mensuration Module 06: Forest Surveying Module 07: Timber Harvesting Part One Module 08: Timber Harvesting Part Two Module 09: Urban Forestry Learning Outcomes Understand the fundamentals of forestry and its ecological significance. Analyze forest ecosystems and their components for conservation purposes. Evaluate forest soil characteristics and their impact on tree growth. Apply principles of silviculture for sustainable forest management practices. Utilize forest mensuration techniques to measure tree growth and biomass. Implement forest surveying methods to assess land and plan management strategies. CPD 10 CPD hours / points Accredited by CPD Quality Standards Forestry: Surveying, Soil, Mensuration and Ecosystem 1:44:34 1: Module 01: Introduction to Forestry 12:33 2: Module 02: Forest Ecosystem 13:14 3: Module 03: Forest Soil 11:15 4: Module 04: Silviculture 13:03 5: Module 05: Forest Mensuration 11:59 6: Module 06: Forest Surveying 13:32 7: Module 07: Timber Harvesting Part One 09:24 8: Module 08: Timber Harvesting Part Two 07:04 9: Module 09: Urban Forestry 11:30 10: CPD Certificate - Free 01:00 Who is this course for? Professionals in environmental science and forestry management sectors. Students pursuing degrees in forestry or related environmental studies. Individuals interested in land management and conservation careers. Forestry technicians seeking to enhance their technical knowledge. Environmental consultants specializing in forest ecosystem assessments. Career path Forest Officer Ecologist Arboriculturist Land Management Consultant Wildlife Conservation Officer Forestry Technician Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

Diploma in Counselling and Psychology Are you concerned about your prospects? Our expertly designed Diploma in Counselling and Psychology course is here to solve all of your problems at once. Learn all the necessary skills to join the psychology & counselling industry with confidence. It is a demanding profession, with the average salary of a Psychologist in the UK around 55,000 GBP. This qualification enables you to pursue a rewarding career in a rapidly growing counselling and psychology sector. Through this Diploma in Counselling and Psychology course, you will gain a thorough understanding of Counselling and Psychology. Learn how to assist people in dealing with personal and professional challenges. There are numerous opportunities to work in well-established institutions and companies. Enrol on our Diploma in Counselling and Psychology course today, become an expert in human minds, and take the first step toward a psychologist or counsellor career. Courses are included in this Diploma in Counselling and Psychology Bundle Course Course 01: Diploma in Counselling and Psychology Course 02: Diploma in Mastering Psychology Course 03: Clinical Psychology Diploma Others Included of Diploma in Counselling and Psychology Bundle Course Free 3 PDF Certificate Access to Content - Lifetime Exam Fee - Totally Free Free Retake Exam [ Note: Free PDF certificate as soon as completing the Diploma in Counselling and Psychology course] Diploma in Counselling and Psychology Detailed course curriculum of the Diploma in Counselling and Psychology Course: Module 01: Introduction: Toward an Integrative Approach in Counselling Module 02: Therapeutic Relationship: Exploring Clients' Symptoms and Strengths Module 03: Powered by Struggles and Strengths Module 04: Positive Psychology in Counselling: What is It? Module 05: Psychoanalytic Therapy Module 06: Adlerian Therapy Module 07: Existential Therapy Module 08: Person‐Centred Therapy Module 09: Gestalt Therapy Module 10: Behaviour Therapy Module 11: Cognitive‐Behaviour Therapy Module 12: Reality Therapy Module 13: Feminist Therapy Module 14: Family Therapy Assessment Method After completing each module of the Diploma in Counselling and Psychology Course, you will find automated MCQ quizzes. To unlock the next module, you need to complete the quiz task and get at least 60% marks. Certification After completing the MCQ/Assignment assessment for this Diploma in Counselling and Psychology course, you will be entitled to a Certificate of Completion from Training Tale. Who is this course for? Diploma in Counselling and Psychology This Diploma in Counselling and Psychology course is suitable for anyone who wants to start a career as a psychologist or counsellor, as well as professionals who want to test their existing skills and knowledge. Requirements Diploma in Counselling and Psychology There are no specific requirements for this Diploma in Counselling and Psychology course because it does not require any advanced knowledge or skills. Career path Diploma in Counselling and Psychology After completing this Diploma in Counselling and Psychology course, candidates may pursue careers. Certificates Certificate of completion Digital certificate - Included

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

Fashion Stylist Fundamentals is a comprehensive theoretical course designed to introduce you to the essential aspects of fashion styling. Starting with an overview of the fashion stylist's role, this course explores the core elements of styling, from fabric selection to conceptual creativity.

CRM: Customer Relationship Management Would you want to learn about various methods for choosing tools and the best ways to keep customers? Our in-depth CRM (Customer Relationship Management) will assist you in expanding your knowledge about the CRM sector. Our CRM (Customer Relationship Management) provides an introduction to Customer Relationship Management (CRM) along with its all functions. Also, the CRM (Customer Relationship Management) explains CRM strategies, and data analysis in CRM and CRM Databases. Moreover, this CRM (Customer Relationship Management) includes difficulties handling processes. Additionally, the CRM (Customer Relationship Management) explain how to deepen the customer relationship and the future of CRM. Enhance your organisational efficiency and maximise business growth through our effective CRM (Customer Relationship Management) practices! Learning Outcome of CRM (Customer Relationship Management) This CRM (Customer Relationship Management) will teach you about: Introduction to CRM (Customer Relationship Management). The CRM (Customer Relationship Management) explains CRM fundamentals. CRM (Customer Relationship Management) also includes CRM strategies. Data analysis in CRM and collecting CRM databases are parts of this CRM (Customer Relationship Management). Through the CRM (Customer Relationship Management), you will learn about deepening customer relationships. Handling customer complaints and the future of CRM is elaborately explained in this CRM (Customer Relationship Management). Special Offers of this CRM: Customer Relationship Management Course This CRM: Customer Relationship Management Course includes a FREE PDF Certificate. Lifetime access to this CRM: Customer Relationship Management Course Instant access to this CRM: Customer Relationship Management Course Get FREE Tutor Support to this CRM: Customer Relationship Management Course CRM: Customer Relationship Management Unlock the full potential of your customer interactions with our CRM: Customer Relationship Management course, offering a comprehensive introduction to CRM strategies and functionalities. This CRM: Customer Relationship Management course guides you through the essentials of CRM, from data analysis to managing CRM databases. Learn how to navigate challenges and streamline processes through the CRM: Customer Relationship Management framework. Moreover, the CRM: Customer Relationship Management course teaches you to deepen customer relationships and explore the future of CRM. Elevate your business and master the art of customer loyalty with our expert-led CRM: Customer Relationship Management program. Who is this course for? CRM: Customer Relationship Management This CRM (Customer Relationship Management) is intended for individuals who wish to enhance their company chances and cultivate solid client connections. Requirements CRM: Customer Relationship Management To enrol in this CRM: Customer Relationship Management Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our CRM: Customer Relationship Management Course. Be energetic and self-motivated to complete our CRM: Customer Relationship Management Course. Basic computer Skill is required to complete our CRM: Customer Relationship Management Course. If you want to enrol in our CRM: Customer Relationship Management Course, you must be at least 15 years old. Career path CRM: Customer Relationship Management You may work as a manager, customer service manager, CRM analyst, and many other roles after finishing this CRM (Customer Relationship Management)!