151 Arithmetic courses in Sheffield delivered On Demand

This course extensively illustrates how to become a skilled JavaScript developer. Working from the fundamentals, you will learn what JavaScript is, what it can do, and why to use it. A range of topics is covered clearly and structured while building practical projects along the way, including real-world examples and mini-challenges.

This course offers an immersive experience in data analysis, guiding you from initial setup with Python and Pandas, through series and DataFrame manipulation, to advanced data visualization techniques. Perfect for enhancing your data handling and analysis skills.

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

Course Overview If you are a JavaScript developer who wants to master TypeScript fundamentals, jumpstart on the road to learning TypeScript with this TypeScript Tutorial For Beginners course.  TypeScript is an open-source programming language which builds on JavaScript. The advantage of Typescript over Javascript is that it adds optimal static typing to the JavaScript language. Many Javascript frameworks use typescript, such as Angular. This course covers a comprehensive set of modules to enhance your understanding of TypeScript fundamentals. It explains what typescript is and gives you a clear understanding of its significance. You will learn how to find the data type of a variable in TypeScript and understand how to define a function type variable typescript. You will also learn how to define objects using classes and use the different access modifiers. In time, you will get to grips with the specific skills to write more scalable applications. Whatever you learn in JavaScript adds value to your understanding of TypeScript. You're already halfway there if you're familiar with Javascript. Enrol right now! Learning Outcomes Understand the variables and data types Explore how to define variables using data types Gain in-depth knowledge of the operators Deepen your understanding of the object oriented principles Know how to create and use arrow functions Familiarise with the flow control statements Understand the variable prefixes Have an in-depth understanding of variable prefixes Who is this course for? The TypeScript Tutorial For Beginners course is incredibly beneficial for professionals interested in understanding the fundamentals of TypeScript. Upgrading skills in this course open doors to tremendous opportunities. 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. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. 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 The TypeScript Tutorial For Beginners course provides useful skills to possess and would be beneficial for any related profession or industry such as: TypeScript Developer Full Stack Developer Unit 01: Introduction Module 01: What and why TypeScript 00:02:00 Module 02: TypeScript Playground 00:04:00 Module 03: Install TypeScript 00:02:00 Module 04: Install Visual Studio Code 00:01:00 Unit 02: Variables and Data Types Module 01: Introduction 00:03:00 Module 02: First Program Using Visual Studio Code 00:04:00 Module 03: Use JS in a HTML 00:02:00 Module 04: Strings 00:02:00 Module 05: Boolean 00:01:00 Module 06: Any Type 00:01:00 Module 07: Homogenous Arrays 00:03:00 Module 08: Heterogenous Arrays 00:01:00 Module 09: Using alert confirm and prompt 00:03:00 Module 10: Comments 00:02:00 Module 11: Enum Type 00:05:00 Unit 03: Operators Module 01: Arithmetic 00:03:00 Module 02: Assignment 00:04:00 Module 03: Comparison 00:04:00 Module 04: Logical 00:04:00 Module 05: Ternary 00:03:00 Unit 04: Flow Control Statements Module 01: Introduction 00:01:00 Module 02: IF Else Ladder 00:06:00 Module 03: Switch 00:04:00 Module 04: Break and Case Flow 00:03:00 Module 05: While loop 00:03:00 Unit 05: Objects and Arrays Module 01: Introduction 00:02:00 Module 02: Object Literal 00:03:00 Module 03: For-In Loop 00:02:00 Module 04: Arrays 00:04:00 Module 05: De-Structuring Arrays 00:02:00 Module 06: De-Structuring Objects 00:02:00 Unit 06: Functions Module 01: Introduction 00:02:00 Module 02: First Function 00:03:00 Module 03: Passing a parameter 00:01:00 Module 04: Passing Multiple Parameters 00:02:00 Module 05: Optional Parameters 00:04:00 Module 06: Default Values 00:01:00 Module 07: Function as parameter 00:02:00 Module 08: Returning a function 00:03:00 Module 09: Anonymous Functions 00:02:00 Module 10: Overloading 00:05:00 Module 11: REST PARAMS 00:05:00 Module 12: Using a Type on REST PARAM 00:01:00 Unit 07: Arrow Functions Module 01: Introduction 00:02:00 Module 02: First arrow function 00:03:00 Module 03: Passing Parameters 00:03:00 Module 04: Array of Arrow Functions 00:03:00 Unit 08: Variable Prefixes Module 01: let 00:03:00 Module 02: const 00:02:00 Module 02: const functions 00:02:00 Module 04: declare 00:01:00 Unit 09: Interfaces Module 01: Introduction 00:02:00 Module 02: Define an Object Interface 00:03:00 Module 03: Create and object 00:03:00 Module 04: Defining optional properties 00:01:00 Module 05: Interfaces are only compile time 00:01:00 Module 06: Function Interfaces 00:04:00 Module 07: Return Types in Functional interfaces 00:02:00 Module 08: Adding methods to Object Interfaces 00:02:00 Module 09: Array Interfaces 00:03:00 Module 10: String indexed Array Interfaces 00:03:00 Module 11: Extending interfaces 00:06:00 Unit 10: Classes Module 01: Introduction 00:01:00 Module 02: Create a class 00:03:00 Module 03: Add a constructor 00:04:00 Module 04: Add Function properties 00:02:00 Module 05: Power of TypeScript 00:01:00 Module 06: Using for-in and instanceof 00:04:00 Module 07: Implementing an interface 00:06:00 Unit 11: Inheritance Module 01: Introduction 00:03:00 Module 02: Extending a class 00:05:00 Module 03: Create Child Objects 00:07:00 Module 04: Inheriting Functionality 00:04:00 Module 05: Overriding 00:03:00 Unit 12: Access modifiers, Encapsulation and Static Module 01: Public and readonly 00:02:00 Module 02: Encapsulation 00:01:00 Module 03: Private properties 00:04:00 Module 04: Accessor methods 00:02:00 Module 05: Using Static Properties 00:04:00 Module 06: More about static 00:01:00 Module 07: Static Methods 00:03:00 Unit 13: Type Casting Module 01: String to numeric 00:04:00 Module 02: Using the toString method 00:03:00 Module 03: Object Casting 00:02:00 Unit 14: Modules Module 01: Introduction 00:01:00 Module 02: Using Function Modules 00:04:00 Module 03: Import Aliasing and Alternate Export Syntax 00:02:00 Module 04: Default Exports 00:02:00 Module 05: Class Modules 00:01:00 Module 06: Aliasing class modules 00:02:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Using Blueprints in UE5, you can learn game development without coding. This beginner-friendly course will teach you how to use Unreal Engine's visual coding system. There is no prior experience required, and each lesson will gradually increase your knowledge.

Introducing the 'Python Programming Bible | Networking, GUI, Email, XML, CGI' - your comprehensive, all-in-one resource for mastering Python! Are you an aspiring developer looking to dive into the ocean of Python programming or a seasoned coder seeking to level up your Python game? Look no further! Our course is expertly designed to take you from the basics to the complexities of Python, including Networking, GUI, Email, XML, and CGI. If you've ever dreamt of not just learning Python but truly mastering it, this is the course for you. This program is designed to provide a solid foundation and sharpen your skills in one of the most in-demand programming languages, while also introducing you to its many applications. This course starts with the basics of Python, providing a gentle yet thorough introduction and setup that caters to beginners as well as those looking to refresh their Python knowledge. As we study deeper into the heart of Python, we dive into objects, classes, and the power of regular expressions. But it doesn't stop there! You'll also become comfortable with concepts like CGI programming, which is an important building block for creating dynamic web pages. Navigating from core programming, we transition into the intricacies of managing databases and executing multithreading in Python. You'll gain the confidence to handle complex data management tasks, understand how Python interacts with databases, and efficiently manages multiple tasks simultaneously. The XML section allows you to get hands-on with parsing, data extraction, and manipulation, while the GUI section unveils the art of creating beautiful, user-friendly interfaces using Python. The course is enriched with a diverse set of resources, including real-world projects, quizzes, and interactive coding exercises. This is more than just a course, it's your passport to a new realm of opportunities, unlocking a world where Python programming is your strength, not just a skill.  So whether you're a student aiming to get a head start on your peers, a professional looking to diversify your skills, or an enthusiast wanting to dive deeper into the Python universe, the Python Programming Bible is the starting point for your journey to becoming a Python expert. Enrol today and step into a future of endless opportunities with Python! Learning Outcomes: Upon completion of the Python Programming Bible course, you should be able to: Understand and implement Python basics and advanced concepts. Build object-oriented programs with Python. Utilise regular expressions for pattern-matching tasks. Develop dynamic web pages using CGI programming. Interact with databases efficiently using Python. Apply multithreading for better utilisation of resources. Process and manipulate data using XML in Python. Design and create user-friendly GUIs with Python. Who is this course for? This Python Programming Bible course is ideal for the following: Beginners aiming to learn Python from scratch. Professionals looking to broaden their programming skills. Students pursuing a degree in Computer Science. Web developers looking to integrate Python into their toolkit. Data enthusiasts aiming to handle data with Python. Career Path: This Python Programming Bible course will help you to develop your knowledge and skills to pursue different careers, such as: Python Developer: (£35,000 - £70,000). Data Analyst: (£27,000 - £55,000). Web Developer: (£24,000 - £60,000). Data Scientist: (£45,000 - £90,000). Machine Learning Engineer: (£50,000 - £90,000). Software Developer: (£30,000 - £70,000). Certification After studying the course materials of the Python Programming Bible | Networking, GUI, Email, XML, CGI 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 free. Original Hard Copy certificates need to be ordered at an additional cost of £8. Prerequisites This Python Programming Bible | Networking, GUI, Email, XML, CGI does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Python Programming Bible | Networking, GUI, Email, XML, CGI 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. Course Curriculum Section 01: Introduction & Setup Introduction 00:02:00 Setup on Mac OS X 00:03:00 Setup On Linux/Ubuntu 00:03:00 Setup On Windows 00:03:00 Run Code Online 00:03:00 Section 02: Basics Comments 00:02:00 Variables & Variable Types 00:05:00 Lists 00:04:00 Tuples 00:03:00 Dictionary 00:06:00 Data Type Conversion 00:02:00 Arithmetic Operators 00:05:00 Comparison Operators 00:03:00 Assignment Operators 00:03:00 Bitwise Operators 00:10:00 Logical Operators 00:07:00 Membership Operators 00:02:00 Identity Operators 00:02:00 Operator Precedence 00:03:00 Decision Making 00:09:00 Loops 00:06:00 Loop Control Statements 00:05:00 Numbers 00:05:00 Strings 00:12:00 Lists In Depth 00:05:00 Tuples In Depth 00:06:00 Dictionary In Depth 00:08:00 Date & Time 00:07:00 Functions 00:11:00 Modules 00:05:00 File Inputs & Outputs 00:13:00 Handling Exceptions 00:07:00 Section 03: Classes/Objects Simple Example 00:04:00 Creating Instance Objects 00:01:00 Accessing Attributes 00:04:00 Constructor New & Init Method 00:06:00 Destroying Objects 00:02:00 Class Inheritance 00:04:00 Overriding Methods 00:03:00 Overloading Methods 00:01:00 Overloading Operators 00:04:00 Data Hiding 00:03:00 Section 04: Regular Expressions Match Function 00:05:00 Search Function 00:02:00 Advanced Expressions 00:05:00 Search & Replace 00:03:00 Section 05: CGI Programming Basic CGI Programming 00:08:00 Get Method 00:06:00 Post Method 00:05:00 Cookies 00:05:00 Section 06: Database Setup Database 00:02:00 Connect To Database 00:05:00 Create Table 00:03:00 INSERT Operation 00:04:00 READ Operation 00:06:00 UPDATE Operation 00:02:00 DELETE Operation 00:02:00 Simple Network Example 00:04:00 Simple Client 00:04:00 Section 07: Multithreading Initiate a New Thread 00:07:00 Create Thread 00:06:00 Synchronise Threads 00:03:00 Multithreaded Priority Queue 00:09:00 Section 08: XML Parse an XML File 00:10:00 Section 09: GUI Introduction 00:02:00 Button Preview 00:03:00 Canvas 00:04:00 Checkbutton 00:02:00 Entry 00:02:00 Frame 00:04:00 Label 00:02:00 List Box 00:02:00 Menu button 00:03:00 Menu 00:08:00 Message 00:02:00 Radio button 00:05:00 Scale 00:03:00 Scrollbar 00:04:00 Text 00:03:00 Top-level 00:02:00 Spinbox 00:02:00 Paned Window 00:03:00 Message Box 00:02:00 Label Frame 00:02:00 Section 10: Resource Resource 00:00:00 Assignment Assignment - Python Programming Bible | Networking, GUI, Email, XML, CGI 00:00:00

Discover the power of data science and machine learning with Python! Learn essential techniques, algorithms, and tools to analyze data, build predictive models, and unlock insights. Dive into hands-on projects, from data manipulation to advanced machine learning applications. Elevate your skills and unleash the potential of Python for data-driven decision-making.

Welcome to this beginner's level course on Microsoft SQL Servers. Understand the concepts of SQL and learn to create a new database and table to perform various operations on it, with live running queries as examples. Work on hands-on exercises and understand database concepts in a real-world scenario.

Overview Embarking on the High School Math course opens doors to a world where numbers and equations form the backbone of countless real-world applications. In an era where data-driven decisions rule, this course stands as a cornerstone for those aspiring to thrive in numerous professional fields.  A recent study by the Educational Research Center highlighted that proficiency in high school mathematics is strongly correlated with success in higher education and various career paths. This course not only equips students with fundamental mathematical knowledge but also sharpens analytical and problem-solving skills, making them indispensable in today's competitive landscape. Venture on a journey of mathematical mastery. Enrol in the High School Math course today and unlock the door to a world of opportunities and intellectual growth! 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 High School Math. It is available to all students, of all academic backgrounds. Requirements Our High School Math 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 12 sections • 136 lectures • 23:03:00 total length •Introduction: 00:03:00 •What is Function?: 00:07:00 •Vertical Line Test: 00:04:00 •Value of a Function Graphically: 00:08:00 •Domain Range of a function Algebraically: 00:13:00 •Domain Range of a function Graphically: 00:06:00 •Even & Odd Functions: 00:07:00 •One to one Function: 00:05:00 •Composite Functions: 00:09:00 •How to draw Rational Functions- 1: 00:04:00 •How to draw Rational Functions- 2: 00:10:00 •Inverse of a function Algebraically: 00:05:00 •Inverse of a function Graphically: 00:09:00 •Practice Problems 1: 00:15:00 •Practice Problems 2: 00:11:00 •Resources Downloads: 00:40:00 •Introduction to Quadratic Equations: 00:04:00 •Solving Quadratic Equations by Factorization method: 00:10:00 •Writing in completed square form: 00:08:00 •Solving by completed square method: 00:08:00 •Sketching of Quadratic Graphs: 00:11:00 •Quadratic graphs using Transformations: 00:06:00 •Quadratic inequalities: 00:11:00 •Deriving Quadratic formula: 00:05:00 •Solving problems using Quadratic Formula: 00:06:00 •Equations reducible to Quadratic: 00:07:00 •Nature of Roots of Quadratic Equations: 00:04:00 •Nature of roots continues: 00:12:00 •Quadratic Equations (Resources): 00:50:00 •Distance formula: 00:15:00 •Mid point formula: 00:05:00 •Gradient of a line: 00:10:00 •Graphing using gradient and y intercept: 00:02:00 •Some standard lines: 00:04:00 •Slope intercept form y = m x +c: 00:05:00 •Intersection of line and parabola: 00:09:00 •Practice Problems from past papers (part 3): 00:12:00 •Sequence and series ( video): 00:08:00 •Arithmetic Sequence: 00:10:00 •General term of an A.P.: 00:07:00 •Finding given term is which term?: 00:05:00 •Writing sequence when two terms are known: 00:08:00 •Condition for three terms to be in A.P.: 00:05:00 •Sum to n terms of A.P.: 00:06:00 •Practice Problems 1 (A.P.): 00:08:00 •Practice problems 3 (A.P.): 00:07:00 •Practice problems 4 (A.P.): 00:10:00 •Geometric Progressions: 00:11:00 •Sum to n terms in G.P.: 00:14:00 •Sum to infinite Terms in G.P.: 00:13:00 •Practice Problems 1 (GP): 00:13:00 •Practice Problems 2 (GP): 00:06:00 •Practice Problems based on AP and GP both: 00:15:00 •Sequence and series Text 1: 00:40:00 •Sequence and series Text 2: 00:55:00 •What is Factorial?: 00:06:00 •n-choose -r problems: 00:06:00 •Properties of n - choose -r: 00:05:00 •Expanding using Binomial Theorem: 00:11:00 •Finding the indicated term in the Binomial expansion: 00:10:00 •Finding the indicated term from end: 00:09:00 •Finding the coefficient for given exponent (index) of the variable: 00:08:00 •Finding the term independent of variable: 00:05:00 •Expanding in increasing and decreasing powers of x: 00:09:00 •Practice problems 1: 00:12:00 •Practice Problems 2: 00:09:00 •Practice problems 3: 00:10:00 •Past papers problems 1: 00:15:00 •Past Paper problems 2: 00:13:00 •Past Paper problems 3: 00:09:00 •Resources in this section: 00:48:00 •What is Derivative?: 00:07:00 •Derivation of formula for Derivative: 00:06:00 •Differentiation by definition or First Principle: 00:06:00 •Power Rule: 00:20:00 •Practice Problems on Power Rule 1: 00:07:00 •Practice Problems on Power Rule 2: 00:07:00 •Practice Problems on Power Rule 3: 00:05:00 •Practice Problems on Power Rule 4: 00:11:00 •Practice Problems on Power Rule 5: 00:07:00 •Tangents and Normals- Basics: 00:12:00 •Practice- Tangents and Normals Part 1: 00:16:00 •Practice- Tangents and Normals Part 2: 00:13:00 •Practice- Tangents and Normals Part 3: 00:11:00 •Practice- Tangents and Normals Part 4: 00:14:00 •Stationary Points - Basics: 00:13:00 •Practice- Increasing Decreasing & Maxima Minima part 1: 00:11:00 •Practice- Increasing Decreasing & Maxima Minima part 2: 00:12:00 •Practice- Increasing Decreasing & Maxima Minima part 3: 00:10:00 •Concavity-Basics: 00:02:00 •Concavity & Second Derivative: 00:08:00 •Second Derivative Test: 00:09:00 •Practice Problems on second derivative: 00:04:00 •Practice Problem of Maxima Minima using second derivative test Part 1: 00:17:00 •Practice Problem of Maxima Minima using second derivative test Part 2: 00:10:00 •Practice Problem of Maxima Minima using second derivative test Part 3: 00:07:00 •Practice Problem of Maxima Minima using second derivative test Part 4: 00:07:00 •Applications of Maxima and Minima Part 1: 00:09:00 •Applications of Maxima and Minima Part 2: 00:07:00 •Applications of Maxima and Minima Part 3: 00:10:00 •Applications of Maxima and Minima Part 4: 00:09:00 •Applications of Maxima and Minima Part 5: 00:10:00 •Applications of Maxima and Minima Part 6: 00:08:00 •Past Paper Problems on applications of maxima and minima Part 1: 00:09:00 •Past Paper Problems on applications of maxima and minima Part 2: 00:09:00 •Past Paper Problems on applications of maxima and minima Part 3: 00:08:00 •Past Paper Problems on applications of maxima and minima Part 4: 00:07:00 •Chain Rule: 00:12:00 •Rate of change part 1: 00:05:00 •Rate of change part 2: 00:10:00 •Rate of change part 3: 00:07:00 •Past Paper Problems using chain rule -1: 00:06:00 •Past Paper Problems using chain rule - 2: 00:07:00 •Past Paper Problems using chain rule 3: 00:07:00 •Past Paper Problems using chain rule -4: 00:04:00 •Graphical Method of solving pair of linear equations: 00:10:00 •Video lecture on Graphical method: 00:05:00 •Method of elimination by substitution: 00:10:00 •Video lecture on substitution method: 00:06:00 •Method of elimination by equating the coefficients: 00:10:00 •Video lecture on equating coefficients method: 00:09:00 •Practice Problems on Linear equation: 00:20:00 •How to take up this course?: 00:10:00 •Background of Algebra: 00:10:00 •Language of Alg ebra: 00:10:00 •Finding Values of algebraic expressions: 00:14:00 •Fractional Indices: 00:10:00 •Higher Indices: 00:07:00 •Rules of Brackets: 00:04:00 •Simplification by removing brackets (BODMAS): 00:11:00 •Simplifications of Algebraic Fractions: 00:07:00 •Solving complex Linear Equations in one variable: 00:10:00 •Factorization by taking out common factor: 00:10:00 •Factorization by grouping the terms: 00:09:00 •Factorize using identity a ² - b ²: 00:07:00 •Factorization by middle term split: 00:12:00

Python Programming: Beginner To Expert Overview Unfold the potential within you, and embark on a journey of mastering Python programming - from the fundamental building blocks to the pinnacle of expertise. This comprehensive course, crafted with meticulous care, empowers you to transform from a curious novice to a confident coding maestro, wielding Python's power with finesse. Within these engaging modules, you'll delve into the core principles of Python, meticulously exploring data types, operators, control flow, and functions. As your proficiency blossoms, you'll conquer advanced topics like object-oriented programming, powerful libraries like NumPy and Pandas, and the art of crafting polished scripts. But this journey isn't merely about acquiring technical prowess; it's about unlocking a world of possibilities. By the course's end, you'll be equipped to embark on a rewarding career path, armed with the skills to tackle real-world challenges in diverse domains - from data analysis and web development to scientific computing and automation. Learning Outcomes Gain a solid foundation in Python syntax, data structures, and control flow mechanisms. Master essential functions, user input, and error-handling techniques. Explore advanced data types, object-oriented programming concepts, and popular libraries like NumPy and Pandas. Craft polished, reusable Python scripts for various applications. Confidently navigate the Python ecosystem and continuously expand your knowledge. Why You Should Choose Python Programming: Beginner To Expert Lifetime access to the course No hidden fees or exam charges CPD Accredited certification on successful completion Full Tutor support on weekdays (Monday - Friday) Efficient exam system, assessment and instant results Download Printable PDF certificate immediately after completion Obtain the original print copy of your certificate, dispatch the next working day for as little as £9. Improve your chance of gaining professional skills and better earning potential. Who is this Course for? Python Programming: Beginner To Expert is CPD certified and IAO accredited. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic backgrounds. Requirements Our Python Programming: Beginner To Expert is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path You will be ready to enter the relevant job market after completing this course. You will be able to gain necessary knowledge and skills required to succeed in this sector. All our Diplomas' are CPD and IAO accredited so you will be able to stand out in the crowd by adding our qualifications to your CV and Resume. Python Programming: Beginner To Expert Module 01: Introduction to Python Programming from A-Z Intro To Python Section Overview 00:06:00 What is Python Programming? 00:10:00 Who is This Course For? 00:05:00 Python Programming Marketplace 00:06:00 Python Job Opportunities 00:05:00 How To Land a Python Job Without a Degree 00:08:00 Python Programmer Job Roles 00:09:00 Python from A-Z Course Structure 00:04:00 Module 02: Getting Familiar with Python Getting Familiar with Python Section Overview 00:06:00 Installing Python on Windows 00:10:00 Anaconda and Jupyter Notebooks Part 1 00:08:00 Anaconda and Jupyter Notebooks Part 2 00:16:00 Comments 00:05:00 Python Syntax 00:02:00 Line Structure 00:03:00 Line Structure Exercise 00:07:00 Joining Lines 00:05:00 Multiple Statements on a Single Line 00:05:00 Indentation 00:08:00 Module 03: Basic Data Types Basic Data Types Section Overview 00:08:00 String Overview 00:10:00 String Manipulation 00:07:00 String Indexing 00:04:00 String Slicing 00:08:00 Printing 00:10:00 Python Variables 00:08:00 Integers and Floats 00:08:00 Booleans 00:02:00 Mini Project 1 : Letter Counter 00:20:00 Module 04: Python Operators Python Operators Section Overview 00:04:00 Comparison Operators 00:09:00 Arithmetic Operators 00:08:00 Assignment Operators 00:05:00 Logical Operators 00:13:00 Identity Operators 00:05:00 Membership Operators 00:02:00 Bitwise Operators 00:08:00 Module 05: Advanced Data Types Python Advanced Data Types Section Overview 00:11:00 Sets 00:06:00 List Overview 00:05:00 List Slicing and Indexing 00:04:00 Tuples 00:02:00 Dictionaries 00:11:00 When to use each one? 00:05:00 Compound Data Types 00:03:00 Module 06: Control Flow Part 1 Control Flow Part 1 Section Overview 00:15:00 Intro to Control Flow 00:01:00 Basic Conditional Statements 00:14:00 More Conditional Statements 00:05:00 For Loops 00:10:00 While Loops 00:12:00 Module 07: Control Flow Part 2 Control Flow Part 2 Section Overview 00:02:00 Break Statements 00:08:00 Continue Statements 00:05:00 Zip Function 00:07:00 Enumerate Function 00:04:00 List Comprehension 00:04:00 Module 08: Python Functions Python Functions Section Overview 00:03:00 Intro to Functions 00:02:00 Python help Function 00:03:00 Defining Functions 00:09:00 Variable Scope 00:08:00 Doc Strings 00:04:00 Module 09: User Input and Error Handling User Input and Error Handling Section Overview 00:02:00 Introduction to error handling 00:03:00 User Input 00:04:00 Syntax Errors 00:04:00 Exceptions 00:11:00 Handling Exceptions Part 1 00:08:00 Handling Exceptions Part 2 00:08:00 Module 10: Python Advanced Functions Python Advanced Functions Section Overview 00:05:00 Lambda Functions 00:05:00 Functions args and kwargs 00:10:00 Iterators 00:08:00 Generators and Yield 00:12:00 Map Function 00:14:00 Filter Function 00:08:00 Module 11: Python Scripting and Libraries Python Scripting and Libraries Section Overview 00:05:00 What is a script? 00:01:00 What is an IDE? 00:17:00 What is a text editor? 00:12:00 From Jupyter Notebook to VScode Part 1 00:15:00 From Jupyter Notebook to VScode Part 2 00:05:00 Importing Scripts 00:03:00 Standard Libraries 00:04:00 Third Party Libraries 00:06:00 Module 12: NumPy NumPy Section Overview 00:04:00 Why use NumPy? 00:04:00 NumPy Arrays 00:10:00 Reshaping, Accessing, and Modifying 00:07:00 Slicing and Copying 00:06:00 Inserting, Appending, and Deleting 00:10:00 Array Logical Indexing 00:04:00 Broadcasting 00:08:00 Module 13: Pandas Intro to Pandas 00:17:00 Pandas Series 00:17:00 Pandas Series Manipulation 00:17:00 Pandas DataFrame 00:17:00 Pandas DataFrame Manipulation 00:13:00 Dealing with Missing Values 00:10:00 Module 14: Introduction to OOP Functional vs OOP 00:06:00 OOP Key Definitions 00:04:00 Create your First Class 00:12:00 How to Create and Use Objects 00:06:00 How to Modify Attributes 00:12:00 Module 15: Advanced OOP Python Decorators 00:27:00 Property Decorator 00:09:00 Class Method Decorator 00:07:00 Static Methods 00:10:00 Inheritance from A to Z 00:21:00 Module 16: Starting a Career in Python Getting Started with Freelancing 00:09:00 Building A Brand 00:12:00 Personal Branding 00:13:00 Importance of Having Website/Blog 00:04:00 Do's and Don'ts of Networking 00:06:00 Creating A Python Developer Resume 00:06:00