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Course Title: Engineering Calculus Made Simple (Derivatives) Are you struggling to grasp the intricacies of calculus and derivatives in your engineering studies? Fear not, because our comprehensive course, 'Engineering Calculus Made Simple (Derivatives),' is designed to demystify the complexities of this crucial subject and empower you with the knowledge and skills needed to excel in your engineering endeavors.   Key Features: Clarity and Simplicity: We understand that calculus, especially derivatives, can be intimidating. Our course breaks down complex concepts into easy-to-understand, bite-sized modules, ensuring that you not only comprehend the material but also gain a deep appreciation for its application in engineering. Real-world Applications: Our instructors bridge the gap between theory and practice by emphasizing real-world applications of derivatives in engineering scenarios. From optimizing design parameters to analyzing dynamic systems, you'll gain insights into how derivatives play a crucial role in solving practical engineering problems. Interactive Learning: Engage in a dynamic learning experience with our interactive sessions, where you'll have the opportunity to solve problems, ask questions, and receive immediate feedback. Our instructors are committed to ensuring your active participation and understanding throughout the course. Expert Instructors: Learn from seasoned professionals and educators with a wealth of experience in both engineering and calculus. Our instructors are dedicated to simplifying complex topics and providing you with the tools to excel in your academic and professional pursuits. Comprehensive Resources: Access a rich repository of resources, including video lectures, practice problems, and supplementary materials. These resources are designed to reinforce your understanding and allow you to revisit key concepts at your own pace. Progressive Learning Path: Our course follows a carefully structured learning path, gradually building your understanding of derivatives from foundational principles to advanced applications. Whether you're a beginner or looking to reinforce your existing knowledge, our course caters to a range of proficiency levels.   Benefits: Gain a solid foundation in derivative concepts and applications. Improve problem-solving skills for engineering scenarios. Boost confidence in tackling calculus-related challenges. Enhance your academic performance and career prospects.   Enroll in 'Engineering Calculus Made Simple (Derivatives)' today and take the first step towards mastering the fundamental tools of engineering calculus. Unleash your potential and build a strong foundation for success in your academic and professional journey. Don't let derivatives be a stumbling block - make them your stepping stones to engineering excellence! Course Curriculum Introduction To Engineering Calculus Made Simple (Derivatives) Course Introduction To Engineering Calculus Made Simple (Derivatives) Course 00:00 Functions Functions 00:00 Limits Limits 00:00 The Derivative The Derivative 00:00 Trig Identities Trig Identities 00:00 The Squeeze Theorem The Squeeze Theorem 00:00 The Derivative Of Sin(X) The Derivative Of Sin(X) 00:00 The Derivative Of Cos(X) The Derivative Of Cos(X) 00:00 Other Derivatives Other Derivatives 00:00

Overview This comprehensive course on Computer Science 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 Computer Science 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 Computer Science With Python. It is available to all students, of all academic backgrounds. Requirements Our Computer Science 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 5 sections • 152 lectures • 04:54:00 total length •Introduction: 00:03:00 •Quiz 1: 00:02:00 •Quiz 1 Solution: 00:01:00 •What is Programming: 00:03:00 •Quiz 2: 00:01:00 •Quiz 2 Solution: 00:01:00 •Meeting the interpreter and Problem Quiz 3: 00:01:00 •Quiz 3 solution: 00:01:00 •Congratulations: 00:01:00 •Why programming and Quiz 4: 00:02:00 •Quiz 4 Solution: 00:03:00 •Grammar and Python Rules: 00:04:00 •Backus Naur Form: 00:03:00 •Quiz 4 part 2: 00:01:00 •Quiz 4 part 2 Solution: 00:01:00 •Python Grammar and Quiz 5: 00:05:00 •Quiz 5 Solution: 00:03:00 •Quiz 6: 00:01:00 •Quiz 6 Solution: 00:02:00 •Processors: 00:02:00 •Introducing Variables: 00:05:00 •Variables Quiz 7: 00:02:00 •Variables Can Vary: 00:03:00 •Variables Quiz 8: 00:01:00 •Quiz 8 Solution: 00:01:00 •Variables Quiz 9: 00:01:00 •Quiz 9 Solution: 00:01:00 •Variables Quiz 10: 00:01:00 •Quiz 10 Solution: 00:03:00 •Introducing Strings: 00:04:00 •Using Strings Quiz 11: 00:01:00 •Quiz 11 Solution: 00:03:00 •Strings and Numbers - String Concatenation Quiz Solution: 00:03:00 •String indexing: 00:02:00 •Quiz 13: 00:01:00 •Quiz 13 Solution: 00:03:00 •String subsequences: 00:04:00 •String subsequences quiz 14: 00:01:00 •Quiz 14 solution: 00:02:00 •Understanding selection quiz 15: 00:01:00 •Quiz 15 solution: 00:04:00 •Finding string in string quiz 16: 00:04:00 •Quiz 16 solution: 00:02:00 •Testing and quiz 17: 00:02:00 •Quiz 17 solution: 00:03:00 •Find With Parameter Quiz 18: 00:02:00 •Quiz 18 solution: 00:01:00 •Extracting links from a web page Quiz 19: 00:03:00 •Extracting links from a web page Quiz 19 Solution: 00:02:00 •Final Quiz: 00:01:00 •Final Quiz Solution: 00:02:00 •Congratulations: 00:01:00 •Unit Overview: 00:03:00 •Procedural Abstraction: 00:03:00 •Introducing Procedures: 00:04:00 •Procedure code quiz 1: 00:04:00 •Quiz 1 Solution: 00:01:00 •Output and quiz 2: 00:01:00 •Quiz 2 Solution: 00:02:00 •Return Statement and Quiz 3: 00:03:00 •Quiz 3 solution: 00:02:00 •Inc Procedure Quiz 4: 00:01:00 •Quiz 4 Solution: 00:01:00 •Sum Procedure and Quiz 5: 00:01:00 •Quiz 5 Solution: 00:02:00 •Sum procedure with a return statement: 00:02:00 •Square procedure quiz 6: 00:01:00 •Quiz 6 Solution: 00:02:00 •Sum 3 Quiz 7: 00:01:00 •Quiz 7 Solution: 00:02:00 •Double string procedure quiz 8: 00:01:00 •Quiz 8 Solution: 00:01:00 •Find second quiz 9: 00:02:00 •Quiz 9 Solution: 00:02:00 •Equality Comparison Quiz 10: 00:04:00 •Quiz 10 Solution: 00:01:00 •If statement quiz 11: 00:03:00 •Quiz 11 Solution: 00:03:00 •Is friend quiz 12: 00:02:00 •Quiz 12 solution: 00:02:00 •Is friend quiz 13: 00:02:00 •Quiz 13 Solution: 00:02:00 •The Or construct: 00:03:00 •Quiz 14 solution: 00:06:00 •While loop quiz 15: 00:05:00 •Quiz 15 solution: 00:03:00 •While loop quiz 16: 00:01:00 •Quiz 16 solution: 00:02:00 •Print numbers quiz 17: 00:01:00 •Quiz 17 solution: 00:02:00 •Factorial quiz 18: 00:02:00 •Quiz 18 solution: 00:02:00 •Break quiz 19: 00:04:00 •Quiz 19 solution: 00:03:00 •Quiz 20: 00:05:00 •Quiz 20 Solution: 00:01:00 •No links quiz 21: 00:01:00 •Print all links quiz 21 solution: 00:03:00 •Final Quiz: 00:01:00 •Final Quiz Solution: 00:02:00 •Unit Overview: 00:03:00 •Stooges and quiz 1: 00:01:00 •Quiz 1 Solution: 00:01:00 •Countries quiz: 00:01:00 •Quiz 3 solution: 00:01:00 •Relative Size Quiz: 00:01:00 •Quiz 4 Solution: 00:01:00 •Lists Mutation: 00:01:00 •Different Stooges quiz: 00:01:00 •Quiz 5 Solution: 00:01:00 •Secret Agent Man Quiz: 00:01:00 •Replace Spy Quiz: 00:01:00 •Quiz 7 Solution: 00:03:00 •Python List Addition and Length: 00:02:00 •List Operations In Python: 00:02:00 •Python lists length quiz: 00:01:00 •Quiz 8 Solution: 00:01:00 •Append Quiz: 00:01:00 •Hard drive quiz: 00:01:00 •Quiz 11 Solution: 00:01:00 •Python Loops on Lists Quiz: 00:02:00 •Quiz 12 solution: 00:02:00 •Python For loops: 00:03:00 •Sum List Quiz: 00:01:00 •Measure a String Quiz: 00:01:00 •Find Element Quiz: 00:02:00 •Quiz 15 solution: 00:04:00 •Quiz 16 solution: 00:01:00 •Python Union Procedure Quiz: 00:01:00 •Quiz 17 solution: 00:01:00 •Pop in Python Quiz 18: 00:02:00 •Quiz 18 solution: 00:03:00 •Collecting Links: 00:01:00 •Get All Links: 00:02:00 •Starting Get All Links Quiz: 00:01:00 •Quiz 19 solution: 00:01:00 •Updating Links Quiz: 00:01:00 •Quiz 20 Solution: 00:01:00 •Finishing Get All Links Quiz: 00:01:00 •Quiz 21 Solution: 00:01:00 •Finishing the Python Web Crawler: 00:03:00 •Crawling Process Quiz: 00:01:00 •Quiz 22 Solution: 00:01:00 •Crawl Web Quiz: 00:01:00 •Quiz 23 Solution: 00:01:00 •Crawl Web Loop Quiz: 00:01:00 •Quiz 24 Solution: 00:02:00 •Crawl If Quiz: 00:01:00 •Quiz 25 Solution: 00:01:00 •Finishing Crawl Web and Final Quiz: 00:02:00 •Final Quiz Solution & Conclusion: 00:03:00 •Assignment - Computer Science With Python: 00:00:00

Overview Two skills which are vital to an administration specialist are Touch Typing and Shorthand. Master these abilities and stand out in any organisation. This popular Touch Typing Essential Skills Level 3 course will teach you the techniques that make these two essential abilities achievable and boost your CV's contents. Both Touch Typing (Keyboard) and Shorthand (Writing) allow an individual to increase the accuracy and productivity of the work they produce. When you pass this certified course and assessments, you will be able to set yourself up for numerous career opportunities. From journalist to a stenographer, and from Personal Assistant to Bookkeeper, all career paths will be possible. How will I get my certificate? At the end of the course there will be an online MCQ test which you can take either during or after the course. After successfully completing the test 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 Touch Typing Essential Skills Level 3. It is available to all students, of all academic backgrounds. Requirements Our Touch Typing Essential Skills Level 3 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 1 sections • 12 lectures • 01:00:00 total length •Module 01: Getting Started: 00:05:00 •Module 02: DRILL 1 The home keys: 00:05:00 •Module 03: DRILL 2 e and i, g and h: 00:05:00 •Module 04: DRILL 3 o and n, shift keys and t: 00:05:00 •Module 05: DRILL 4 extra practice . and y: 00:05:00 •Module 06: DRILL 5 , and w: 00:05:00 •Module 07: DRILL 6 m and u: 00:05:00 •Module 08: DRILL 7 v and x: 00:05:00 •Module 09: DRILL 8 sentence drills: 00:05:00 •Module 10: DRILL 9 figures: 00:05:00 •Module 11: DRILL 10 alphabetical paragraphs: 00:05:00 •Module 12: Recap: 00:05:00

Overview This comprehensive course on Interpersonal Skills in Management will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Interpersonal Skills in Management 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 Interpersonal Skills in Management. It is available to all students, of all academic backgrounds. Requirements Our Interpersonal Skills in Management 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 1 sections • 12 lectures • 01:41:00 total length •Module 01: What are Soft Skills?: 00:09:00 •Module 02: Communication: 00:06:00 •Module 03: Teamwork: 00:06:00 •Module 04: Problem-Solving: 00:06:00 •Module 05: Time Management: 00:07:00 •Module 06: Attitude and Work Ethic: 00:07:00 •Module 07: Adaptability/Flexibility: 00:06:00 •Module 08: Self-Confidence (Owning It): 00:08:00 •Module 09: Ability to Learn From: 00:06:00 •Module 10: Networking: 00:06:00 •Module 11: Employee Relations: 00:15:00 •Module 12: Motivation and Counselling: 00:19:00

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Description: This diploma in C++ and Python programming course is a great way to get started in programming. It covers the study of the C++ and Python group of languages used to build most of the world's object oriented systems. The course is for interested students with a good level of computer literacy who wish to acquire programming skills. It is also ideal for those who wish to move to a developer role or areas such as software engineering. This is a great course to develop your coding skills. It teaches key features of imperative programming using C and is an ideal preliminary to the Object-Oriented Programming using Python. Join the course now! Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Assessment:  At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Python 3 Beginners Module 01 Introduction FREE 00:29:00 Starter Examples 00:33:00 Learning C Concepts 00:13:00 Module 02 Data Types and Inference 00:20:00 Sizeof and IEEE 754 00:33:00 Constants L and R Values 00:11:00 Operators and Precedence 00:25:00 Literals 00:26:00 Module 03 Classes and Structs FREE 00:22:00 Enums 00:14:00 Unions 00:16:00 Introduction to Pointers 00:11:00 Pointers and Array Indexing 00:12:00 Using Const with Pointers 00:09:00 Pointers to String Literals 00:12:00 References 00:14:00 Smart Pointers 00:22:00 Arrays 00:15:00 Standard Library Strings 00:13:00 More Standard Library Strings 00:18:00 Functions 00:06:00 More Functions 00:16:00 Function Pointers 00:15:00 Control Statements 00:18:00 Python 3 Intermediate Module 04 Installing Python FREE 00:17:00 Documentation 00:30:00 Command Line 00:17:00 Variables 00:29:00 Simple Python Syntax 00:15:00 Keywords 00:18:00 Import Module 00:17:00 Additional Topics 00:23:00 Module 05 If Elif Else 00:31:00 Iterable 00:10:00 For 00:11:00 Loops 00:20:00 Execute 00:05:00 Exceptions 00:18:00 Data Types 00:24:00 Module 06 Number Types 00:28:00 More Number Types 00:13:00 Strings 00:20:00 More Strings 00:11:00 Files 00:08:00 Lists 00:15:00 Dictionaries 00:04:00 Tuples 00:07:00 Sets 00:09:00 Module 07 Comprehensions 00:10:00 Definitions 00:02:00 Functions 00:06:00 Default Arguments 00:06:00 Doc Strings 00:06:00 Variadic Functions 00:07:00 Factorial 00:07:00 Function Objects 00:07:00 Module 08 Lambda 00:11:00 Generators 00:06:00 Closures 00:10:00 Classes 00:09:00 Object Initialization 00:05:00 Class Static Members 00:07:00 Classic Inheritance 00:10:00 Data Hiding 00:07:00 Python 3 Advanced Iterators and Generators FREE 00:16:00 Regular Expressions 00:19:00 Introspection and Lambda Functions 00:27:00 Metaclasses and Decorators 00:24:00 Modules and Packages 00:25:00 Working with APIs 00:15:00 Metaprogramming Primer 00:19:00 Decorators and Monkey Patching 00:21:00 XML and JSON Structure 00:10:00 Generating XML and JSON 00:17:00 Parsing XML and JSON 00:19:00 Implementing Algorithms 00:19:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Audio Typing: Audio Typing Are you looking to boost your audio typing skills? If you are interested, you can try our comprehensive audio typing course. Participants of the audio typing course learn touch typing techniques and improve listening skills. Moreover, the audio typing course, students familiarise themselves with transcription software. The audio typing curriculum includes exercises to enhance typing speed and accuracy. Additionally, the audio typing course describes strategies for managing complex audio recordings. Students in audio typing course also gain knowledge about formatting, proofreading, and editing transcribed documents. Through this audio typing course, you can prepare for roles in transcription services across various industries. Join our audio typing course to learn the necessary skills for transcribing spoken words into written text efficiently and accurately. Learning outcome of audio typing course This audio typing course teaches: Introduction to audio typing and basics of audio typing. This audio typing course teaches typing techniques & speed enhancement. Audio typing text-to-speech, formatting, and guidelines for transcription are included in this audio typing course. Through the audio typing course, you can specialise in transcription and transcription tools. Quality controlling and proofreading will be taught by this comprehensive audio typing course. You will find opportunities for transcription and proficiency with homophones as part of this audio typing course. Special Offers of this Audio Typing: Audio Typing Course This Audio Typing: Audio Typing Course includes a FREE PDF Certificate. Lifetime access to this Audio Typing: Audio Typing Course Instant access to this Audio Typing: Audio Typing Course Get FREE Tutor Support to this Audio Typing: Audio Typing Course Audio Typing: Audio Typing Touch typing techniques are explained in the audio typing course. Along with improving their listening skills, participants in the audio typing course also learn how to use transcription software. Additionally, the training on audio typing includes strategies for dealing with challenging audio recordings. Additionally, typing exercises to increase accuracy and speed are covered in this audio typing course. Students that enroll in the audio typing course also learn how to format, proofread, and edit transcribed papers. Who is this course for? Audio Typing: Audio Typing Students, recent graduates, and job seekers might benefit from this audio typing course. Requirements Audio Typing: Audio Typing To enrol in this Audio Typing: Audio Typing Course, students must fulfil the following requirements. To join in our Audio Typing: Audio Typing Course, you must have a strong command of the English language. To successfully complete our Audio Typing: Audio Typing Course, you must be vivacious and self driven. To complete our Audio Typing: Audio Typing Course, you must have a basic understanding of computers. A minimum age limit of 15 is required to enrol in this Audio Typing: Audio Typing Course. Career path Audio Typing: Audio Typing Many employment options, including those for audio typists, legal secretaries, medical transcriptionists, and many more, will become available with the purchase of this bundle that combines audio typing course.

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

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Game Developer: Average salary range £30,000 - £60,000 Course Curriculum Section 01: Introduction Course Introduction 00:02:00 Course Curriculum 00:04:00 How to get Pre-requisites 00:02:00 Getting Started on Windows, Linux or Mac 00:01:00 Section 02: Introduction To Python And Setting Up Introduction to Python 00:02:00 Python vs Other Languages 00:04:00 Why It's Popular 00:04:00 Command Line Basics 00:07:00 Python Installation (Step By Step) 00:06:00 PyCharm IDE Installation 00:08:00 Getting Start PyCharm IDE 00:05:00 First Python Hello World Program 00:07:00 Assessment Test1 00:01:00 Solution for Assessment Test1 00:01:00 Summary 00:02:00 Section 03: PythonBasic Introduction 00:02:00 Variables 00:16:00 Data Types 00:13:00 Type Casting 00:07:00 User Inputs 00:08:00 Comments 00:04:00 Assessment Test2 00:01:00 Solution for Assessment Test2 00:02:00 Summary 00:02:00 Section 04: Python Strings Introduction 00:02:00 Strings 00:05:00 String Indexing 00:05:00 String Slicing 00:04:00 String Built-in Functions 00:09:00 Formatting String (Dynamic Data) 00:05:00 Assessment Test 00:01:00 Solution for Assessment Test 00:01:00 Summary 00:01:00 Section 05: Python Operators Introduction 00:03:00 Arithmetic Operators 00:08:00 Assignment Operators 00:05:00 Comparison Operators 00:05:00 Logical Operators 00:02:00 AND Operator 00:04:00 OR Operator 00:02:00 NOT Operator 00:03:00 Booleans 00:02:00 Assessment Test4 00:02:00 Solution for Assessment Test4 00:01:00 Summary 00:01:00 Section 06: Python Sequences Introduction 00:02:00 Arrays in Earlier 00:02:00 Lists 00:06:00 Add List Items 00:03:00 Remove List Items 00:01:00 Sort Lists 00:03:00 Join Lists 00:08:00 Tuples 00:08:00 Update tuples 00:07:00 Join tuples 00:02:00 Dictionaries 00:06:00 Add Dictionary Items 00:04:00 Remove Dictionary Items 00:03:00 Nested Dictionaries 00:04:00 Sets 00:04:00 Add Set Items 00:03:00 Remove Set Items 00:01:00 Join Set Items 00:04:00 Assessment Test 00:01:00 Solution for Assessment Test 00:02:00 Summary 00:01:00 Section 07: Python Statements Introduction 00:03:00 If Statement 00:03:00 If-else Statement 00:04:00 If-elif-else Statement 00:04:00 If Statement Coding Exercise 00:05:00 Assessment Test 00:02:00 Solution for Assessment Test 00:02:00 Summary 00:02:00 Section 08: Python Control Flow Statements Introduction 00:04:00 Flow Charts 00:04:00 While Loops Statement 00:10:00 For Loops Statement 00:06:00 Loop through a String 00:03:00 The Break Statement 00:03:00 The Continue Statement 00:02:00 The range() Function 00:04:00 Nested Loops 00:04:00 2D List using Nested Loop 00:04:00 Assessment Test 00:01:00 Solution for Assessment Test 00:03:00 Summary 00:01:00 Section 09: Python Games For Beginners Introduction 00:01:00 Guessing Game 00:07:00 Car Game 00:10:00 Summary 00:01:00 Section 10: Python Functions Introduction 00:02:00 Creating a Function 00:03:00 Calling a Function 00:06:00 Function with Arguments 00:05:00 args, Arbitrary Arguments 00:04:00 kwargs, Arbitrary Keyword Arguments 00:06:00 Summary 00:01:00 Section 11: Working With File Structure Introduction 00:03:00 Reading Files 00:10:00 Creating / Writing Files 00:06:00 Delete Files 00:03:00 Summary 00:01:00 Section 12: Regular Expressions Introduction 00:02:00 RegEx Module 00:07:00 RegEx Functions 00:08:00 Summary 00:02:00 Section 13: PythonProject Introduction 00:02:00 Project Overview 00:03:00 ATM RealTime Project 00:13:00 Summary 00:01:00