A carefully structured course that covers everything from installing Git on Linux to understanding Git reset such as soft, mixed, and hard reset. With a perfect blend of animations and live lab demos, the course makes it easy to grasp the concepts.
Overview From automation to complex data analysis, Python is used in a wide range of tasks. Thus, to become a high-demand professional in the IT industry, you must build a solid foundation in this programming language. Our Python for Beginners is the perfect place to start enhancing your knowledge and skills in this area. Through the comprehensive course, you will get a primary understanding of Python. The informative modules will help you understand the data types and data structure. You will receive detailed lessons on control flow and operators. After that, the modules will equate you to the basics of Python arrays, iterators and generators. Finally, you will get a clear understanding of the functions and file manipulation. After the completion of the course, you will receive a certificate of achievement. This certificate will help you elevate your resume. Course Preview Learning Outcomes Introduce yourself to the basics of Python Familiarise yourself with the data types and operators Enhance your understanding of data structures and control flow Explore the vital areas of Python arrays, iterators and generators Develop a clear understanding of functions and file manipulation Why Take This Course From John Academy? Affordable, well-structured and high-quality e-learning study materials Engaging tutorial videos, materials from the industry-leading experts Opportunity to study in a user-friendly, advanced online learning platform Efficient exam systems for the assessment and instant result Earn UK & internationally recognised accredited qualification Easily access the course content on mobile, tablet, or desktop from anywhere, anytime Excellent career advancement opportunities Get 24/7 student support via email. What Skills Will You Learn from This Course? Python Who Should Take This Python for Beginners Course? Whether you're an existing practitioner or an aspiring professional, this course is an ideal training opportunity. It will elevate your expertise and boost your CV with key skills and a recognised qualification attesting to your knowledge. Are There Any Entry Requirements? This Python for Beginners is available to all learners of all academic backgrounds. But learners should be aged 16 or over to undertake the qualification. And a good understanding of the English language, numeracy, and ICT will be helpful. Certificate of Achievement After completing this course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates & Transcripts can be obtained either in Hardcopy at £14.99 or in PDF format at £11.99. Career Pathâ This exclusive Python for Beginners will equip you with effective skills and abilities and help you explore career paths such as Web Developer Data Analyst Software Developer Game Developer Course Introduction Python for Beginners Introduction 00:01:00 Module 01: Getting Started with Python Why Learn Coding 00:05:00 Why Learn Python 00:04:00 Gearing Up Linux Machine For Python Programming 00:15:00 Gearing Up Windows For Python 00:13:00 Integrate Python And Git Bash With Vscode 00:03:00 Gearing Up The Macos For Python Programming 00:06:00 Installing Jupyter Notebook In Windows 00:06:00 Hello World In Jupyter Notebook 00:11:00 Module 02: Data Types and Operators Arithmetic Operators 00:14:00 Order Of Evaluation 00:09:00 Variable And Assignment Operators 00:12:00 Correct Variable Names 00:08:00 Integer Float And Complex Numbers In Python 00:11:00 Boolean Comparison Operator And Logical Operator 00:20:00 Strings In Python 00:07:00 Type And Type Casting 00:10:00 String Methods In Python 00:09:00 Taking Input From User 00:05:00 Exercise 1 00:09:00 Module 03: Data Structures Lists In Python 00:16:00 Necessitites In List 00:14:00 List Methods 00:19:00 Tuples In Python 00:14:00 Sets In Python 00:14:00 Dictionary, Mutable, Accessing Items 00:08:00 Dublicates, Constructor And Data Types In Dictionary 00:06:00 Access And Add Items In Dictionaries 00:06:00 Nested Dictionaries And Dictionary Methods 00:10:00 Exercise 2 00:12:00 Module 04: Control Flow Introduction 00:01:00 Conditional Statements 00:10:00 Short Hand If Else 00:10:00 Nested If 00:05:00 For Loops 00:13:00 While Loops In Python 00:07:00 While Vs For Loop 00:07:00 Break Continue Statment 00:07:00 Try And Except 00:07:00 Exercise 3 00:07:00 Module 05: Functions Intro To Functions 00:05:00 Arguments, Parameters And Multiple Arguments 00:09:00 Arbitrary Arguments, Keyword Arguments, Arbitrary Keyword Arguments 00:10:00 Default Parameter Value And Passing A List As Parameters 00:09:00 Return Values And Pass Statements 00:06:00 Exercise 4 00:09:00 Module 06: Python Arrays, Iterators and Generators Array, Length Of Array, Accessing Elements Of Array 00:10:00 Adding, Removing Elements In Array, Array Methods 00:12:00 Iterator In Python 00:14:00 Generators In Python 00:07:00 Exercise 5 00:07:00 Module 07: File Manipulation File Hancdling And Syntax 00:05:00 Reading The File, Line Extraction And Parsing 00:11:00 Appending And Writing The Files In Python 00:06:00 Create And Delete A File 00:05:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00
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Learn to program with Python 3, visualize algorithms and data structures, and implement them in Python projects
About the course “Quantum Computing for Finance” is an emerging multidisciplinary field of quantum physics, finance, mathematics, and computer science, in which quantum computations are applied to solve complex problems. “Introduction to Quantitative and Computational Finance” provides a basis to step into the world of Quantum Computing for Finance. This introductory course will develop fundamental concepts required for an understanding of quantum algorithms and more advanced topics in computational finance. Through this course, you will learn the basics of derivative products, the Black-Scholes-Merton model for pricing vanilla derivatives, and how to compute the price of exotic options with a computer. This course is designed for all those who wish to develop their skills and start a career in quantitative finance. This course is the first part of the specialised training program: “Quantum Computing for Finance”. What Skills you will learn The fundamentals of derivative products, their types – forwards and options, and their pricing. An understanding of the Black-Scholes-Merton model, hedging and volatility modelling. The computational and modelling techniques for pricing options such as Monte-Carlo simulations and the Finite Difference method. A strong foundation in quantitative and computational skills for modelling and solving complex financial problems using Python programming language. The skills for a career in the finance industry, including quantitative asset management and trading, financial engineering, risk management, and applied research. Course Prerequisites All potential learners should have prior knowledge of the following content areas, either through completion of academic studies or relative professional preparation: Basic calculus (partial derivatives) Probability theory (with an exposure to measure theory if possible) Basic linear algebra (matrix operations) Numerical Python (NumPy essentially) The course contains several Python based programming exercises. We recommend that you install Python on your local system to practice and implement the programs explained throughout the course. For instructions and tutorials for beginners, please click on the following link: Python installation instructions and tutorials for beginners Duration The estimated duration to complete this course is approximately 4 weeks (~3hrs/week). Course assessment To complete the course and earn certification, you must pass all the quizzes at the end of each lesson by scoring 80% or more. Instructors QuantFiQuantFi is a French start-up research firm formed in 2019 with the objective of using the science of quantum computing to provide solutions to the financial services industry. With its staff of PhD's and PhD students, QuantFi engages in fundamental and applied research in in the field of quantum finance, collaborating with industrial partners and universities in seeking breakthroughs in such areas as portfolio optimisation, asset pricing, and trend detection.
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This Bundle Consists of the following Premium courses: Course 01: Machine Learning with Python Course 02: Advanced Diploma in User Experience UI/UX Design Course 03: Data Science & Machine Learning with R Course 04: Python Programming for Everybody Course 05: Data Structures Complete Course Course 06: Data Science with Python Course 07: Computer Science: Graph Theory Algorithms Course 08: Higher Order Functions in Python - Level 03 Course 09: AWS Essentials Course 10: Cloud Computing / CompTIA Cloud+ (CV0-002) Course 11: Introduction to Data Analysis So, enrol now to advance your career! Benefits you'll get choosing Apex Learning for this Machine Learning: One payment, but lifetime access to 11 CPD courses Certificate, student ID for the title course included in a one-time fee Full tutor support available from Monday to Friday Free up your time - don't waste time and money travelling for classes Accessible, informative modules taught by expert instructors Learn at your ease - anytime, from anywhere Study the course from your computer, tablet or mobile device CPD accredited course - improve the chance of gaining professional skills How will I get my Certificate? After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificate: Free (Previously it was £10 * 11 = £110) Hard Copy Certificate: Free (For The Title Course) If you want to get hardcopy certificates for other courses, generally you have to pay £20 for each. 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Curriculum of the Bundle Course 01: Machine Learning with Python Module 01: Introduction to Algorithms Module 02: Preprocessing Module 03: Regression Module 04: Classification Course 02: Data Science & Machine Learning with R Data Science and Machine Learning Course Intro Data Types and Structures in R Data Types and Structures in R Intermediate R Data Manipulation in R Data Visualization in R Creating Reports with R Markdown Building Webapps with R Shiny Introduction to Machine Learning Starting A Career in Data Science Course 03: Python Programming for Everybody Module 01 A Installing Python Documentation Command Line Variables Simple Python Syntax Keywords Import Module Module 02 Additional Topics If Elif Else Iterable For Loops Execute Exceptions Module 03 Data Types Number Types More Number Types Strings More Strings Files Lists Dictionaries Tuples Sets Module 04 Comprehensions Definitions Functions Default Arguments Doc Strings Variadic Functions Factorial Module 05 Function Objects Lambda Generators Closures Classes Object Initialization Class Static Members Classic Inheritance Data Hiding Course 04: Advanced Diploma in User Experience UI/UX Design UX/UI Course Introduction Introduction To The Web Industry Foundations of Graphic Design UX Design (User Experience Design) UI Design (User Interface Design) Optimization Starting a Career in UX/UI Design Course 05: Data Structures Complete Course Unit 01: Introduction Unit 02: Arrays Unit 03: Liked List Unit 04: Stack Unit 05: Queues Unit 06: Priority Queues (PQs) Unit 07: Union Find Unit 08: Binary Search Trees Unit 09: Fenwick Tree Unit 10: Hash Tables Unit 11: Suffix Array Unit 12: AVL Trees Unit 13: Indexed Priority Queue Unit 14: Sparse Tables Course 06: Data Science with Python Unit 01: Introduction to Python Data Science Unit 02: Data Cleaning Packages Unit 03: Data Visualization packages Course 07: Computer Science: Graph Theory Algorithms Module 00: Promo Module 01: Introduction Module 02: Common Problem Module 03: Depth First Search Module 04: Breadth First Search Module 05: Breadth First Search Shortest Path on a Grid Module 06: Trees Module 07: Topological Sort Module 08: Dijkstra Module 09: Bellman-Ford Algorithm Module 10: Floyd-Warshall Algorithm Module 11: Bridge and Algorithm Points Module 12: Tarjan Algorithm Module 13: Travelling Salesman Problem (TSP) Module 14: Eulerian Paths and Circuits Module 15: Prim's Minimum Spanning Tree Algorithm Module 16: Network Flow Course 08: Higher Order Functions in Python - Level 03 Module 01: Course Introduction Module 02: Simple Higher Order Functions Module 03: Sorting with Keys Module 04: Map Function Module 05: Filter Function Module 06: List Comprehension Alternative Module 07: Recursion Introduction Course 09: AWS Essentials Section 01: AWS Foundations and Services Section 02: AWS Security and Costs Course 10: Cloud Computing / CompTIA Cloud+ (CV0-002) Section 01: What You Need to Know Section 02: Introducing the Cloud Section 03: System Requirements for Cloud Deployments Section 04: Cloud Storage Section 05: Cloud Compute Section 06: Cloud Networking Section 07: Cloud Security Section 08: Migrating to the Cloud Section 09: Maintaining Cloud Solutions Section 10: Troubleshooting Cloud Solutions Course 11: Introduction to Data Analysis Module 01: Introduction Module 02: Agenda and Principles of Process Management Module 03: The Voice of the Process Module 04: Working as One Team for Improvement Module 05: Exercise: The Voice of the Customer Module 06: Tools for Data Analysis Module 07: The Pareto Chart Module 08: The Histogram Module 09: The Run Chart Module 10: Exercise: Presenting Performance Data Module 11: Understanding Variation Module 12: The Control Chart Module 13: Control Chart Example Module 14: Control Chart Special Cases Module 15: Interpreting the Control Chart Module 16: Control Chart Exercise Module 17: Strategies to Deal with Variation Module 18: Using Data to Drive Improvement Module 19: A Structure for Performance Measurement Module 20: Data Analysis Exercise Module 21: Course Project Module 22: Test your Understanding CPD 125 CPD hours / points Accredited by CPD Quality Standards Who is this course for? 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