22632 Improv courses

Overview Learn effective business research methods and develop a more productive supply chain to enhance profitability, by enrolling in our exclusively designed Logistics and Supply Chain Management course.This course will equip you with strong management skills to supervise storage and distribution of goods in a company, and handle industrial challenges and trends to ensure business profitability and customer satisfaction.All successful companies demand skilled supply managers for generating large product volumes on time, using cost-effective techniques. After your successful completion, you will be far more capable of using logistics while making lucrative decisions, matching the operations to established budgets, tracking the transfer process of supplies, materials, and more. Make sure you're ready to manage supply chains during a time of crisis. 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 Logistics and Supply Chain Management. It is available to all students, of all academic backgrounds. Requirements Our Logistics and Supply Chain Management is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 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 Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management , Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 3 sections • 25 lectures • 14:20:00 total length •Course Overview: 00:05:00 •Getting Started: 00:15:00 •The Evolution of the Supply Chain: 00:15:00 •The Basic Supply Chain Structure: 00:15:00 •Supply Chain Drivers: 00:15:00 •Aligning Your Supply Chain with Business Strategy: 00:15:00 •Managing Supply Chain Risks: 00:15:00 •Tracking and Evaluating Supply Chain Data: 00:30:00 •Troubleshooting Supply Chain Problems: 00:15:00 •Sharing Supply Chain Activities: 00:15:00 •Sustainable Supply Chain Strategies: 00:15:00 •Applying Lean Techniques to the Supply Chain: 00:15:00 •The Future of Supply Chain Management: 00:15:00 •Module One - Getting Started: 00:30:00 •Module Two - Understanding Lean: 01:00:00 •Module Three - Liker's Toyota Way: 01:00:00 •Module Four - The TPS House: 01:00:00 •Module Five - The Five Principles of Lean Business: 01:00:00 •Module Six - The First Improvement Concept (Value): 01:00:00 •Module Seven - The Second Improvement Concept (Waste): 01:00:00 •Module Eight - The Third Improvement Concept (Variation): 01:00:00 •Module Nine - The Fourth Improvement Concept (Complexity): 01:00:00 •Module Ten - The Fifth Improvement Concept (Continuous Improvement): 01:00:00 •Module Eleven - The Improvement Toolkit: 00:30:00 •Module Twelve - Wrapping Up: 01:00:00

The purpose of this course is to assist you in improving your British English pronunciation so that you can become an expert speaker of English.

Overview This comprehensive course on Train the Trainer will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Train the Trainer comes with accredited certification, 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? After successfully completing the course you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this Train the Trainer. It is available to all students, of all academic backgrounds. Requirements Our Train the Trainer 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 Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 35 sections • 98 lectures • 18:47:00 total length •Introduction to Trainer Bootcamp: 00:13:00 •What Makes a Great Trainer?: 00:18:00 •Make Them Feel Safe Before Class Introduction: 00:05:00 •Make Comfortable Small Talk - Part 1: 00:17:00 •Make Comfortable Small Talk - Part 2: 00:20:00 •Make Comfortable Small Talk - Activity Feedback: 00:09:00 •Make an Impressive First Impression: 00:15:00 •Give Last Minute Reminders - Part 1: 00:19:00 •Give Last Minute Reminders - Part 2: 00:15:00 •Give Your Introduction - Part 1: 00:18:00 •Give Your Introduction - Part 2: 00:20:00 •Give Your Introduction - Part 3: 00:00:00 •Find Out About Them: 00:18:00 •Reveal the Takeaways: 00:13:00 •Set Boundaries and Expectations - Part 1: 00:18:00 •Set Boundaries and Expectations - Part 2: 00:06:00 •Give the Lesson Hook: 00:07:00 •Do an Oral Review - Part 1: 00:17:00 •Do an Oral Review - Part 2: 00:04:00 •Send Them to Break: 00:04:00 •Walk and Talk During Break: 00:11:00 •Bring Them Back From Break: 00:13:00 •Workbook - Train the Trainer - Part 1: 00:00:00 •Introduction: 00:11:00 •Build Pre-Activity Credibility and Rapport: 00:15:00 •Hook the Trainees on the Activity - Part 1: 00:15:00 •Hook the Trainees on the Activity - Part 2: 00:12:00 •Craig Czarnecki - 1-3 Get Buy-In for the Activity: 00:06:00 •Craig Czarnecki - 1-1 Part 1 Activity - Get Buy In for the Activity: 00:11:00 •Craig Czarnecki - 2-1 Find Trainees Who Need Help: 00:10:00 •Craig Czarnecki - 2-2 Find Trainees Who Need Help: 00:19:00 •Craig Czarnecki - 2-3 Activity Find Trainees Who Need Help: 00:18:00 •Craig Czarnecki - 3-1 Activity Tutor Effectively During Activities: 00:17:00 •Craig Czarnecki - 3-2 Tutor Effectively During Activities: 00:11:00 •Craig Czarnecki - 3-3 Tutor Effectively During Activities: 00:20:00 •Craig Czarnecki - 3-4 Activity Tutor Effectively During Activities: 00:19:00 •Craig Czarnecki - 3-5 Activity Tutor Effectively During Activities: 00:09:00 •Craig Czarnecki - 4-1 Manage the Activity Pace: 00:17:00 •Craig Czarnecki - 4-2 Activity Manage the Activity Pace: 00:14:00 •Craig Czarnecki - 5 Activity Prepare to Lead an Activity: 00:18:00 •Craig Czarnecki - Activity Highlight Video: 00:00:00 •Workbook - Training on Facilitating Classroom Activity: 00:00:00 •0.1 Craig Czarnecki - Coach Intro Part 1: 00:19:00 •0.2 Craig Czarnecki - Coach Intro Part 2: 00:07:00 •1.1 Craig Czarnecki - Coach Learn About the Trainer - Recognize the Trainers Strengths: 00:13:00 •1.2 Craig Czarnecki - Coach Learn About the Trainer - Gauge areas for improvement: 00:07:00 •1.3 Craig Czarnecki - Coach Learn About the Trainer - Identify what's Important to the trainer: 00:03:00 •1.4 Craig Czarnecki - Coach Identify the Trainers Style: 00:01:00 •2.1 Craig Czarnecki - Coach Create Initial Value for the Trainer - Create Deliverables for the kickoff meeting: 00:08:00 •2.2 Craig Czarnecki - Coach Create Initial Value for the Trainer - Create a hook for the kickoff meeting: 00:10:00 •2.3 Craig Czarnecki - Coach Create Initial Value for the Trainer - Prepare for the kickoff meeting: 00:07:00 •3.1.1 Craig Czarnecki - Make a Good First Impression - Build a Teammate Relationship Immediately Part 1: 00:10:00 •3.1.2 Craig Czarnecki - Make a Good First Impression - Build a Teammate Relationship Immediately Part 2: 00:14:00 •3.1.3 Craig Czarnecki - Make a Good First Impression - Build a Teammate Relationship Immediately Part 3: 00:16:00 •3.2.1 Craig Czarnecki - Make a Good First Impression - Discuss the Process for Trainer Growth Part 1: 00:12:00 •3.2.2 Craig Czarnecki - Make a Good First Impression - Discuss the Process for Trainer Growth part 2: 00:12:00 •4.1 Craig Czarnecki - Observe the Trainer in the Classroom - Prepare for the Classroom Observation: 00:15:00 •4.2.1 Craig Czarnecki - Observe the Trainer in the Classroom - Master 7 Keys to Effective Note-Taking Part 1: 00:14:00 •4.2.2 Craig Czarnecki - Observe the Trainer in the Classroom - Master 7 Keys to Effective Note-Taking Part 2: 00:14:00 •4.3 Craig Czarnecki - Observe the Trainer in the Classroom - Apply 4 Quick Steps to Classroom Oberserations: 00:09:00 •4.4.1 Craig Czarnecki - Observe trainer activity part 1: 00:19:00 •4.4.2 Craig Czarnecki - Observe trainer activity part 2: 00:18:00 •5.1.1 Craig Czarnecki - Write a Classroom Observation Summary - Identify Strengths and Areas for Improvement Part 1: 00:12:00 •5.1.2 Craig Czarnecki - Write a Classroom Observation Summary - Identify Strengths and Areas for Improvement part 2: 00:13:00 •5.2.1 Craig Czarnecki - Write a Classroom Observation - Record Strengths and Areas for Improvement Part 1: 00:19:00 •5.2.2 Craig Czarnecki - Write a Classroom Observation - Record Strengths and Areas for Improvement Part 2: 00:17:00 •5.2.3 Craig Czarnecki - Write a Classroom Observation - Record Strengths and Areas for Improvement Part 3: 00:18:00 •5.3 Craig Czarnecki - Write a Classroom Observation - Record the Main Strength of the Trainer: 00:35:00 •Introduction and Welcome: 00:00:00 •Open Well: 00:27:00 •Communicate Effectively: 00:15:00 •Provide In Class Support: 00:17:00 •Workbook - Train the Trainer Coliseum: How to Train Very Large Classes: 00:00:00 •Introduction and Welcome: 00:19:00 •Take Good Care Of Yourself: 00:06:00 •Manage Your Stress: 00:09:00 •Anticipate Unexpected Issues: 00:08:00 •Get Help And Make It Helpful: 00:00:00 •Help Them Get It: 00:14:00 •Manage Large Classes: 00:09:00 •Have Fun Your Way: 00:13:00 •Control Tough Customers: 00:10:00 •Engage Adult Students With Ease: 00:02:00 •Interpret Your Feedback: 00:02:00 •Wrap Up Questions And Answers: 00:04:00 •Introduction and Welcome: 00:06:00 •Hog-Tie the Talk Hogs: 00:20:00 •Give the Experts the Spotlight: 00:12:00 •Simmer Down the Know-it-Alls: 00:11:00 •Placate Resenters - Part 1: 00:11:00 •Placate Resenters - Part 2: 00:14:00 •Handle the Fault-Finders: 00:11:00 •Shut Down the Hecklers: 00:10:00 •Stimulate Stubborn Passivists: 00:06:00 •Engage the Distracted Inefficient: 00:07:00 •Workbook - Train the Trainer Serenity Course: 00:00:00 •Assignment - Train the Trainer: 00:00:00 •Order Your Certificate: 00:00:00

Course Overview: Crack the Business Efficiency Code: Diploma in Lean Process and Six Sigma Millions saved, empires built. That's the power of Lean Process and Six Sigma. This isn't just a course; it's your launchpad. Go deeply into Lean's core: grasp its culture, principles, and value vs. waste. Master Value Stream Mapping and unlock the magic of flow and pull. Then, conquer Six Sigma. Master each phase, from defining problems to controlling solutions. Become the cost-saving genius and the efficiency expert. Enrol now. Lead the business transformation. Key Features of the Course: CPD certificate upon successful completion. 24/7 Learning Assistance for continuous guidance. Engaging and contemporary learning materials. Who is This Course For? This diploma in Lean Process and Six Sigma is ideal for aspiring process improvement specialists, business analysts, managers, and those keen to understand the intricacies of Lean and Six Sigma for organisational enhancement. Learning Outcome Gain an insightful understanding of the lean methodology. Recognise the intrinsic values and principles of Lean Culture. Discern the Five Principles of Lean and their application. Distinguish between Value and Waste in processes. Master the art of Value Stream Mapping (VSM). Learn the Principles of Flow and Pull. Acquire a comprehensive overview of Six Sigma. Navigate through the Six Sigma phases from Define to Control with confidence. Why Enrol in This Course: Stay ahead in the dynamic world of business by mastering process improvement skills. This Diploma in Lean Process and Six Sigma is a top-reviewed offering that has recently been updated and aligned with the latest trends. It is your ticket to achieving operational excellence. Requirements: Basic understanding of business processes. Familiarity with management principles is beneficial but optional. Career Path: Lean Process Consultant - Avg. UK salary: £45,000. Six Sigma Specialist - Avg. UK salary: £50,000. Operations Analyst - Avg. UK salary: £42,000. Quality Assurance Manager - Avg. UK salary: £55,000. Process Improvement Manager - Avg. UK salary: £53,000. Business Process Manager - Avg. UK salary: £52,000. Continuous Improvement Director - Avg. UK salary: £70,000. Certification: Learners will be awarded an accredited CPD certificate upon completing the Diploma in Lean Process and Six Sigma course. Course Curriculum 12 sections • 12 lectures • 03:31:00 total length •Understanding Lean: 00:22:00 •The Lean Culture: 00:19:00 •The Five Principles of Lean: 00:10:00 •Value and Waste: 00:19:00 •Value Stream Mapping (VSM): 00:19:00 •The Principles of Flow and Pull: 00:14:00 •Overview of Six Sigma: 00:12:00 •The Define Phase: 00:17:00 •The Measure Phase: 00:21:00 •The Analyse Phase: 00:23:00 •The Improve Phase: 00:21:00 •The Control Phase: 00:14:00

Overview This comprehensive course on Advance Lean Six Sigma Black Belt Course will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Advance Lean Six Sigma Black Belt Course comes with accredited certification, 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 Advance Lean Six Sigma Black Belt Course. It is available to all students, of all academic backgrounds. Requirements Our Advance Lean Six Sigma Black Belt Course 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 Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 10 sections • 36 lectures • 11:04:00 total length •Course Overview: 00:08:00 •Introduction: 00:15:00 •Introduction Part 2: 00:17:00 •Define: 00:25:00 •Define Part 2: 00:20:00 •Measure: 00:13:00 •Measure Part 2: 00:28:00 •Measure Part 3: 00:24:00 •Measure Part 4: 00:17:00 •Measure Part 5: 00:17:00 •Measure Part 6: 00:26:00 •Measure Part 7: 00:24:00 •Measure Part 8: 00:10:00 •Analyze: 00:14:00 •Analyze Part 2: 00:17:00 •Analyze Part 3: 00:28:00 •Analyze Part 4: 00:18:00 •Analyze Part 5: 00:35:00 •Analyze Part 6: 00:27:00 •Analyze Part 7: 00:38:00 •Analyze Part 8: 00:42:00 •Analyze Part 9: 00:33:00 •Analyze Part 10: 00:15:00 •Analyze Part 11: 00:15:00 •Analyze Part 12: 00:16:00 •Improve: 00:23:00 •Improve Part 2: 00:12:00 •Improve Part 3: 00:10:00 •Improve Part 4: 00:23:00 •Improve Part 5: 00:15:00 •Control: 00:17:00 •Control Part 2: 00:08:00 •Case Study: 00:10:00 •Conclusion: 00:04:00 •Resources - Advance Lean Six Sigma Black Belt Course: 00:00:00 •Assignment - Advance Lean Six Sigma Black Belt Course: 00:00:00

Our ISO 9001:2015 QMS Clauses Awareness course is a comprehensive program covering all ten clauses of the standard.

The Kettlebell Foundational Workshop is a comprehensive training program designed to teach the fundamentals of kettlebell exercises. This workshop provides participants with an in-depth understanding of proper technique and form, as well as safety guidelines for using kettlebells effectively. Ideal for fitness enthusiasts and personal trainers, this workshop offers valuable insights into the benefits of incorporating kettlebells into any workout routine. Join us today to learn how to master the art of kettlebell training!

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

Overview Mastering data science skills and expertise can open new doors of opportunities for you in a wide range of fields. Learn the fundamentals and develop a solid grasp of Python data science with the comprehensive Data Science with Python course. This course is designed to assist you in securing a valuable skill set and boosting your career. This course will provide you with quality training on the fundamentals of data analysis with Python. From the step-by-step learning process, you will learn the techniques of setting up the system. Then the course will teach you Python data structure and functions. You will receive detailed lessons on NumPy, Matplotlib, and Pandas. Furthermore, you will develop the skills for Algorithm Evaluation Techniques, visualising datasets and much more. After completing the course you will receive a certificate of achievement. This certificate will help you create an impressive resume. So join today! 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? This course Data Science with Python course is ideal for beginners in data science. It will help them develop a solid grasp of Python and help them pursue their dream career in the field of data science. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush. Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst And much more! Course Curriculum 90 sections • 90 lectures • 10:19:00 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: 00:04:00 •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: 00:06:00 •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

Overview This comprehensive course on English as a Foreign Language will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This English as a Foreign Language 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 English as a Foreign Language. It is available to all students, of all academic backgrounds. Requirements Our English as a Foreign Language 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 Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 7 sections • 32 lectures • 04:49:00 total length •Introduction: 00:04:00 •How to Improve Vocabulary: 00:20:00 •Phrasal Verbs Lecture: 00:09:00 •Phrasal Verbs: 00:36:00 •Reading Tips: 00:04:00 •Reading Practice Example: 00:11:00 •Reading Practice - Learning Pronunciation: 00:03:00 •How to Improve Listening Skills: 00:14:00 •Novak Djokovic Interview: 00:12:00 •MLK Speech: 00:08:00 •George Foreman Interview: 00:11:00 •Michael Jordan Speech: 00:09:00 •Dolph Lundgren Speech: 00:06:00 •Roger Federer Interview: 00:07:00 •Neil Degrasse Tyson Interview: 00:08:00 •Kobe Bryant Interview: 00:08:00 •Lisa Kudrow Interview: 00:07:00 •Courteney Cox Interview: 00:06:00 •Yvonne Orji Interview: 00:07:00 •David Schwimmer Interview: 00:07:00 •Listening Practice: 00:07:00 •Listening Tips: 00:05:00 •How to speak fluently in English: 00:03:00 •How to improve speaking skills: 00:10:00 •Speaking Practice: 00:07:00 •Speaking Tips: 00:08:00 •How to improve writing skills: 00:10:00 •Writing Practice: 00:05:00 •Writing Tips: 00:04:00 •How to maintain the advanced level: 00:10:00 •Final Lecture: 00:23:00 •Assignment - English as a Foreign Language: 00:00:00