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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.

Embark on a Mathematical Odyssey: Build Your Math Fundamentals Welcome to a transformative journey through the enchanting realm of numbers and calculations with our Build Your Math Fundamentals course. Dive deep into the core of mathematical understanding as we unravel the mysteries of integers, factors, fractions, and more. The journey begins with the exploration of directed numbers and meanders through the intricacies of BODMAS, rational numbers, percentages, and beyond. Each module is a stepping stone, laying the foundation for a solid understanding of math fundamentals. No longer view math as a challenge; embrace it as a fascinating adventure with real-world applications. Whether you're a novice eager to conquer the basics or someone looking to refresh their mathematical prowess, this course is your key to unlocking the magic of numbers. Learning Outcomes Master the concept of integers, including directed numbers and their applications. Explore the world of factors, multiples, and their significance in mathematical calculations. Gain proficiency in working with fractions and understand their role in real-world scenarios. Apply the BODMAS rule for simplification with confidence and precision. Navigate through decimal numbers, rational numbers, percentages, and advanced topics like scientific notation. Why choose this Build Your Math Fundamentals course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Build Your Math Fundamentals course for? Students seeking to strengthen their foundational math skills. Professionals wanting to enhance their quantitative abilities. Parents supporting their children in math studies. Job seekers preparing for numerical assessments. Anyone looking to build a solid mathematical foundation for future learning. Career path Data Entry Clerk: £18,000 - £25,000 Administrative Assistant: £20,000 - £28,000 Retail Sales Associate: £18,000 - £22,000 Customer Service Representative: £18,000 - £25,000 Junior Accountant: £22,000 - £30,000 Banking Associate: £20,000 - £28,000 Prerequisites This Build Your Math Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Build Your Math 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. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Integers ( Directed Numbers) Introduction 00:02:00 Number system 00:09:00 Integers and ordering of integers 00:07:00 Addition and Subtractions of Integers 00:10:00 Operations on Integers 00:06:00 Multiplication and Division of Integers 00:07:00 Powers of Integers (Exponents) 00:04:00 Factors and Multiples Complete knowledge about factors and multiples 00:07:00 Divisibility tests for 2,3,4,5,6 00:07:00 Divisibility rules 7,8,9,10,11 00:11:00 Prime Factorization 00:13:00 Highest common factor HCF 00:13:00 Word problems based on HCF 00:12:00 Least common multiple LCM 00:16:00 Relation between lcm and HCF 00:04:00 Fractions Classification of Fractions 00:04:00 Convert mixed to improper and improper to mixed fractions 00:03:00 Equivalent Fractions 00:04:00 Comparing Fractions after converting to like fractions 00:09:00 Reducing a fraction to lowest term 00:04:00 Addition and subtraction OF fractions 00:08:00 Multiplication and division of fractions 00:11:00 Word problems on fractions 00:16:00 Simplification Rule : BODMAS Bodmas and rules to remove brackets 00:03:00 simplify expressions using BODMAS rules 00:05:00 simplify expressions involving fractions using BODMAS 00:07:00 Decimal numbers Decimal numbers in relation to fractions 00:08:00 Like and unlike Decimals 00:05:00 Ordering of Decimal numbers 00:10:00 Addition and subtraction of Decimal 00:07:00 Multiplication of Decimal 00:03:00 Division of Decimal 00:08:00 Rational Numbers Rational number 00:02:00 Representation of Rational Numbers on Number line 00:05:00 Determining which fraction is terminating or non-terminating 00:07:00 shortcut method of writing decimal expansion of fraction to decimal 00:08:00 Approximation Rounding to whole number 00:06:00 Rounding to required number of decimals (1 d.p. ) 00:05:00 Rounding to significant digits 00:07:00 Practice question on three methods of approximation 00:05:00 Estimation and Scientific Notation or Standard form Estimation 00:05:00 Scientific Notation 00:07:00 Operation on numbers when they are in scientific notation 00:06:00 Percentage Percentage to fraction and fraction to percentage 00:06:00 Percentage of a quantity and conversation to decimal 00:06:00 Expressing one quantity as percentage of another quantity 00:06:00 Finding increase decrease percent 00:05:00 Uses of Percentages-Word Problems 00:09:00 Ratio and Proportion Ratio- How to express as simple ratio 00:09:00 How to compare Ratios 00:04:00 Word problems on finding ratios 00:07:00 To divide a given quantity into a given Ratio 00:11:00 Proportion 00:04:00 Practice problems on Proportion 00:06:00 Continued proportion 00:06:00 Unitary Method and its Applications Direct Variation (or proportion) 00:04:00 Problems based on Direct proportion 00:10:00 Inverse Variation (or proportion) 00:10:00 Multiple Ratios 00:10:00 Profit , Loss, discount and Tax Basics - Profit and Loss 00:04:00 More practice problems on Profit _ Loss 00:06:00 Selling price formula and Problems 00:04:00 Cost price formula and Problems 00:03:00 Higher problems on Profit and Loss 00:08:00 Basics - Discount 00:05:00 Practice problems on Discount 00:04:00 Tax 00:06:00

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

Embark on a captivating journey into the realm of Python 3 Programming with our comprehensive course. From unraveling the mysteries of mathematical operators to mastering advanced topics like threading and socket terminology, this course is your gateway to the dynamic world of coding. Engage with hands-on sessions, explore the power of Python libraries, and conquer the art of class implementation. Your digital odyssey begins with the basics and evolves into a sophisticated understanding of programming essentials. Our creatively crafted curriculum promises an exhilarating learning experience, making coding accessible to enthusiasts and novices alike. Learning Outcomes Master the fundamentals of Python 3, from basic math operations to complex string manipulations. Develop practical skills in working with lists, dictionaries, and advanced string manipulation techniques. Gain proficiency in file handling, regex, and navigating systems using the OS library. Understand the principles of classes, inheritance, and the manipulation of date and time. Explore advanced topics such as performing HTTP requests, socket programming, and sending emails using SMTPlib. Why choose this Python 3 Programming course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Python 3 Programming course for? Individuals eager to start their coding journey without prior programming experience. Students seeking a comprehensive understanding of Python 3 programming. Professionals looking to enhance their skills and stay relevant in the evolving tech landscape. Coding enthusiasts excited to explore the vast possibilities Python 3 offers. Anyone desiring a hands-on and engaging learning experience in programming. Career path Python Developer: £35,000 - £55,000 Data Analyst: £30,000 - £50,000 Software Engineer: £40,000 - £65,000 Machine Learning Engineer: £45,000 - £70,000 Web Developer: £32,000 - £50,000 Network Programmer: £38,000 - £60,000 Prerequisites This Python 3 Programming does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Python 3 Programming 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. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Section 01 Welcome to Python 3 course! 00:03:00 Why you should learn Python 3 00:04:00 Installing Python 3 on Windows 00:08:00 Installing Python3 on Ubuntu and Mac 00:08:00 Taking a closer look at Python 3 IDLE 00:05:00 Section 02 Math operators 00:12:00 Strings 00:08:00 Variables and variable naming rules 00:11:00 Our first program! 00:12:00 Type, Len, Str, Int, Float , functions 00:09:00 True or false Boolean 00:10:00 IF statement 00:05:00 IF & ELSE 00:13:00 Using ELIF for multiple statements 00:09:00 While loop 00:16:00 Using Continue in a loop 00:06:00 FOR loop 00:10:00 Importing Python libraries 00:12:00 Section 03 Defining functions in Python 3 00:15:00 Local and global variables 00:10:00 Coding guess the number program 00:16:00 Reverse a string function 00:07:00 Calculate area of a circle program 00:11:00 Simple Python calculator 00:15:00 Removing vowels from string program 00:13:00 Find the largest number out of three 00:16:00 Section 04 Python 3 lists 00:15:00 Creating smaller out of bigger list 00:09:00 Manipulating lists and elements 00:08:00 Append, insert, remove, sort 00:11:00 Tuples 00:13:00 Introduction to dictionaries 00:11:00 Values, keys, items, get 00:08:00 Dictionary comprehension - part 1 00:08:00 Dictionary comprehension - part 2 00:07:00 Advance string manipulation 00:12:00 Upper(), lower(), isupper(), islower() 00:09:00 Split, strip, join, startswith, endswith 00:13:00 Section 05 Navigating through system with OS library 00:29:00 Reading and writing to files 00:16:00 Reversing text from a file 00:17:00 Section 06 Try and except 00:13:00 Section 07 Classes 00:22:00 Changing class attributes 00:10:00 Built in class attributes 00:08:00 Using your class in a different program 00:05:00 Using your class in a program 00:26:00 Implementing students count option 00:05:00 Class inheritance 00:12:00 Overriding methods in a class 00:08:00 Section 08 Printing and calculating date and time 00:30:00 Different date formats 00:09:00 Section 09 Extracting useful data 00:23:00 Regex - part 1 00:23:00 Regex - part 2 00:17:00 Section 10 Performing HTTP GET request 00:20:00 Performing post request 00:04:00 Handling website redirections 00:03:00 BeautifulSoup 00:29:00 Encoding in requests 00:12:00 Session and cookies 00:21:00 SSL certificate, authentication 00:21:00 Json library and proxies 00:10:00 Section 11 Socket terminology 00:09:00 Connecting two machines 00:21:00 Coding a chat program 00:35:00 Receiving Desired Amount of Data 00:20:00 Socket Timeout and Options 00:08:00 UDP Server & Client 00:13:00 AF_UNIX & Raw sockets 00:14:00 Section 12 Theory Behind Threaded Server 00:15:00 Thread & Threading 00:50:00 Section 13 Sending Emails Using SMTPlib 00:32:00 PDF Files 00:11:00 Images In Python 00:16:00 Assignment Assignment - Python 3 Programming 00:00:00

Dive into the captivating world of programming with our course titled 'Python Basic Programming for Absolute Beginners'. Whether you're a novice looking to embark on a new journey or someone eager to grasp the foundational elements of Python, this course is tailored for you. From setting up Python to crafting your first game and understanding the intricacies of control flow statements, our comprehensive curriculum ensures you grasp every fundamental aspect, setting a robust foundation for your future coding endeavours. Learning Outcomes Understand the core concepts and foundational elements of Python programming. Develop proficiency in working with Python strings, operators, and sequences. Master the art of creating control flow statements and basic Python games. Gain insights into file structures and the application of regular expressions in Python. Successfully complete a Python project, showcasing your newfound knowledge. Why buy this Python Basic Programming for Absolute Beginners? 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 Python Basic Programming for Absolute Beginners 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 Python Basic Programming for Absolute Beginners for? Beginners with no prior knowledge of programming seeking a structured introduction. Individuals with a curiosity to explore coding as a new skill or hobby. Students desiring to enhance their academic learning with foundational programming knowledge. Professionals from diverse fields looking to broaden their skill set. Educators wishing to acquire beginner-level knowledge for instructional purposes. Prerequisites This Python Basic Programming for Absolute Beginners does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Python Basic Programming for Absolute Beginners 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 Python Developer: Average salary range £45,000 - £70,000. Data Analyst: Average salary range £30,000 - £55,000. Web Developer: Average salary range £25,000 - £50,000. Software Engineer: Average salary range £35,000 - £75,000. Automation Tester: Average salary range £40,000 - £65,000. 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

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