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The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Complete Python Machine Learning & Data Science Fundamentals there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Complete Python Machine Learning & Data Science Fundamentals course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals 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. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. 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 00:08:00 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 Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 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 00:07:00 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 - Python Machine Learning & Data Science Fundamentals 00:00:00

In this course, you will learn how to author machine learning models in Python without the aid of frameworks or libraries from scratch. Discover the process of loading data, evaluating models, and implementing machine learning algorithms.

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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.

Best Price Of The Market Get Hard Copy + PDF Certificates + Transcript + Student ID Card worth £160 as a Gift - Enrol Now Are you interested in learning more about the viability of pursuing a career as a team physician? Or are you curious to know more about the current role of medicine in sports? This Sports Medicine course will take you through an in-depth analysis of the practice and application of treatment in the sporting world. This Sports Medicine course will teach you about the fundamentals of sports medicine. You will learn about common injuries and medical problems faced by athletes. Furthermore, you will gain knowledge about nutrition and weight management, performance enhancement methods and sports medicine careers. Finally, you will gain many insights into the future of sports science. So enrol in the Sports Medicine course now and gain knowledge about state-of-the-art treatment. Along with this Sports Medicine course, you will get 10 premium courses, an originalhardcopy, 11 PDF certificates (Main Course + Additional Courses) Student ID card as gifts. This Sports Medicine Bundle Consists of the following Premium courses: Course 01: Sports Medicine Fundamentals Course 02: Sports Psychology Course 03: Sports Injuries Course 04: Sports and Fitness Coaching Course 05: Pain Management Course 06: Core Stability Course 07: Science-Based Workout: Build Muscle, Lose Fat & Get Fit Course 08: TRX Bodyweight Workout - Fat Loss & Muscle Building Training Course 09: HIIT: High Intensity Interval Training Course 10: Weight Loss - Intermittent Fasting Course 11: First Aid Training Learning Outcomes: Get to know the fundamentals of sports medicine. Learn about common injuries related to sports. Acquire knowledge about nutrition and weight management. Recognise medical problems faced by athletes. Know in detail about imaging in sports. Learn the methods of performance enhancement. Gain knowledge about careers in sports medicine. Discover the future of sports science. Enrol now in Sports Medicine to advance your career, and use the premium study materials from Apex Learning. Curriculum of this Bundle Course 01: Sports Medicine Fundamentals Module 1: Sports Medicine Module 2: Careers in Sports Medicine Module 3: Top Ten Common Injuries Module 4: Common Medicines Module 5: Nutrition and Weight Management Module 6: Medical Problems Faced by Athletes Module 7: Sports and Exercise Module 8: Imaging in Sports Medicine Module 9: Performance Enhancement Module 10: The Future of Sports Science Course 02: Sports Psychology Module 01 - Introduction Module 02 - Mental Toughness Module 03 - Imagery Module 04 - Motivation in sport Module 05 - Goal Setting in Sport Module 06 - Arousal, Stress, and Anxiety Module 07 - Arousal Regulation Module 08 - Concentration Module 09 - Exercise and Psychological Wellbeing Module 10 - Athletic Injuries and Psychology And Much More... Course 03: Sports Injuries Module 01: Introduction Module 02: Top Ten Common Injuries Module 03: Other Injuries Related to Sports and their Treatment Module 04: Internal Organ Injuries and their Treatment Module 05: First Aid Module 06: Medicine Module 07: Anatomy and Physiology of Sports Injuries Module 08: Drugs and Doping in Sport Module 09: Medical Assessment and Pre-participation Screening And Much More... Course 04: Sports and Fitness Coaching Module 1: Introduction Module 2: Psychological, Motivational, and Behavioural Training for Sports Module 3: Techniques for Sports Coaching Module 4: Physical Fitness and Training Module 5: Management Skills Module 6: Coaching for Popular Sports Module 7: Nutrition Concerns for Athletes Module 8: Injury Prevention and Rehabilitation Module 9: Children and Parent in Sports Module 10: Women Coaches Module 11: Coaching and Ethical Practice Course 05: Pain Management Module 01: Introducing Pain Management Module 02: Pain Theories Module 03: Types of Pain Module 04: Physiology and Psychology of Acute Pain Module 05: Pain as a Long-term Condition Module 06: Back and Neck Pain Module 07: Headache Module 08: Neuropathic Pain and Its Management Module 09: Cancer Pain Module 10: Assessment of Pain Module 11: Relaxation for Pain Management Course 06: Core Stability Module 01: Course Speaking Module 02: Anti-Extension Easy Module 03: Anti-Extension Hard Module 04: Anti-Extension Medium Module 05: Anti-Rotation Easy Module 06: Anti-Rotation Hard Module 07: Anti-Rotation Medium Module 08: Bear Crawl Exercises Module 09: Hip Easy Module 10: Hip Hard Module 11: Hip Medium Module 12: Scapula Easy Module 13: Scapula Medium Module 14: Testing Course 07: Science-Based Workout: Build Muscle, Lose Fat & Get Fit Introduction The Science Behind Building Muscle & Losing Fat Beginner Workout Program Motivation & Goal Setting Course 08: TRX Bodyweight Workout - Fat Loss & Muscle Building Training Introduction TRX Fundamentals Your TRX Workout Exercise Videos TRX And Cardio Boosting Your Results Course 09: HIIT: High Intensity Interval Training Module 01: Introduction to HIIT Module 02: What Is HIIT? Module 03: The Benefits of HIIT Module 04: The Essentials of HIIT Module 05: Fat Loss & Muscle Gain with HIIT Module 06: Build Endurance with HIIT Module 07: Common HIIT Mistakes Module 08: Best Diet for HIIT Module 09: Supplements for HIIT Module 10: Final Ideas & Tips Course 10: Weight Loss - Intermittent Fasting Beginning Concepts & Benifits How Intermittent Fasting Works Intermittent Fasting Protocol Getting Started & Maximizing Results Intermittent Fasting Q & A Final Ideas & Tips Course 11: First Aid Training Introduction to Workplace First Aid Legal Framework for Workplace First Aid Incident Management at Work Primary Survey Secondary Survey Basic First-Aid Techniques Dealing with Minor Injuries at the Workplace Secondary Illness Loss of Responsiveness and CPR Secondary Illness Breathing Problems Secondary Illnesses and Injuries Dealing With Fractures and Dislocations Call for an Emergency How will I get my Certificate? After successfully completing the 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 £10 * 11 = £110) Hard Copy Certificate: Free (For The Title Course) PS The delivery charge inside the UK is £3.99, and the international students have to pay £9.99. CPD 110 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Sports Medicine bundle. Requirements This Sports Medicine course has been designed to be fully compatible with tablets and smartphones. Career path Sports medicine is in high demand. By 2029, 72,500 additional jobs in the field of medicine are anticipated to be filled. Over the following few years, this amounts to a 2.15 percent yearly increase. There are various opportunities for you in this area. On average, you can expect to earn a salary of at least £40,257 annually in the UK. Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - Included

Description Do you need to lead one-on-one meetings in your workplace? If you do, then you will know it is your responsibility to make them comfortable for both of you, and also an effective use of time. One-on-One Meetings Serve Many Purposes They may be for Goal setting Performance review - formal and informal Tasking and progress monitoring Briefing Problem-solving and addressing issues Care and support Guidance Coaching or mentoring Performance feedback ...Even reprimands   But often, people get promoted to a level where they need to lead these kinds of meeting, without getting any training. So, in this course, we'll cover: The different types of one-on-one meeting Planning and preparing your meeting Putting together an effective agenda How to build rapport How men and women each perceive a mixed meeting - with advice for each How to listen well Questioning skills How to adapt to the range of meeting types you'll need as a manager, project manager, or team leader.   As a result, you'll be able to: Select the most effective style for your one-on-one meeting Plan and prepare for an effective meeting that puts both of you at ease, and allows you to make the progress you need Lead a meeting that flows naturally Choose the most suitable room layout for your meeting Build and strengthen professional rapport with the other person Avoid the traps of the male-female one-on-one dynamic Listen deeply, and ask insightful questions Lead a range of different types of one-on-one meeting, for: appraisal, progress checking, coaching, mentoring and reprimands.   Prior Experience The only prior experience you need is some exposure to organizational life. However, the people who may find this most valuable are those who have tried leading their first one-on-one meetings and so know what challenges you want to work on..   Who is this course for? Supervisors who need to guide and support colleagues Managers who need to set expectations, and monitor performance Professionals who need to meet with other professionals and workplace contacts Leaders who want to coach, mentor, and give feedback to colleagues ... anyone in the world of work who has to take the lead in a one-on-one meeting   Your Tutor: Dr Mike Clayton Your tutor is Dr. Mike Clayton. As a senior manager at international consulting firm, Deloitte, Mike had to deal with conflict among staff, and with clients, and even among clients. But more important, as a senior representative of his firm and a program leader, he needed to avoid escalation of conflict. Now, as a trainer and facilitator, he has been applying what he learned and teaching it to others. This course represents 15 years' experience of what tools students find most helpful, and 25 years experience in business, managing conflicts large and small. Mike is supported by Felicity Dwyer Felicity is an experienced management trainer and coach, whose Institute of Leadership and Management accredited courses have a justifiably high reputation across the UK. What Will I Learn? Select the most effective style for your one-on-one meeting Plan and prepare for an effective meeting that puts both of you at ease, and allows you to make the progress you need Lead a meeting that flows naturally Choose the most suitable room layout for your meeting Build and strengthen professional rapport with the other person Avoid the traps of the male-female one-on-one dynamic Listen deeply, and ask insightful questions Lead a range of different types of one-on-one meeting, for: appraisal, progress checking, coaching, mentoring and reprimands. Who is the target audience? Supervisors who need to guide and support colleagues Managers who need to set expectations, and monitor performance Professionals who need to meet with other professionals and workplace contacts Leaders who want to coach, mentor, and give feedback to colleagues ... anyone in the world of work who has to take the lead in a one-on-one meeting Requirements You should be a professional, manager, or supervisor who leads one-on-one workplace meetings ...or be expecting to lead them in the near future. Welcome and Introduction Welcome to the Course 00:03:00 Why One-on-One Meetings are so Important 00:03:00 Reasons to Meet 00:03:00 Meetings are Conversations: Types of Conversation 00:04:00 Preparation and Planning for Your One-onOne Meeting Planning your One-on-One Meetings 00:04:00 How to Prepare for Your Meeting 00:02:00 Preparing your Agenda 00:05:00 Running Your One-on-One Meeting The Five Stages of a Meeting 00:04:00 Meeting Room Layout 00:06:00 Rapport Building Skills 00:04:00 The Male-Female Dynamic 00:01:00 The Male-Female Dynamic - from His Perspective 00:05:00 The Male-Female Dynamic - from Her Perspective 00:02:00 Questioning Skills 00:08:00 Listening Skills 00:06:00 Particular Types of One-on-One Meeting Staff-focused One-on-One Meetings 00:05:00 Checkpoint Meetings 00:04:00 Informal Feedback Meeting 00:04:00 Formal Appraisal Meetings 00:06:00 Difficult Conversations 00:04:00 Coaching Meetings 00:06:00 Mentoring Meetings 00:04:00 Giving a Reprimand 00:03:00 Closing Last Thoughts 00:02:00