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15 Jul, 2025 00:00:03 AM

1. What are the various advantages of DBMS?2. What is meant by Data Independence?3. What is the meaning of Data Redundancy?4. What is meant by Data Integrity?5. What is the meaning of Data Integration?6. What is Data Consistency?7. What is the need of data backup?8. What are the various security measures used by DBMS to ensure data security?9. What is the meaning of scalability?10. What is meant by vertical scaling and horizontal scaling?11. What is meaning of scaling down?12. Which are the key methods used by DBMS to achieve concurrent access to data?13. What is meant by locking?14. What is the meaning of Read Lock and Write Lock?15. What is the benefit of locks used by DBMS?16. What is the meaning of Isolation levels?17. Which are the four isolation levels defined in the SQL standard?18. Which is the lowest Isolation Level?19. What is Read Committed Isolation level?20. What is the function of Repeatable Read Isolation level?21. Which is the highest isolation level?22. Write one difference between Highest Isolation levels and Lower Isolation levels?23. What are the various benefits of using a DBMS over traditonal file-based systems?24. DBMS or traditional file system provides for regular automated backups?25. DBMS supports point-in-time recovery. What is the meaning of point-in-time recovery?26. Which system is better for data analysis - DBMS or File system?27. What are the various disadvantages of DBMS?28. Whether DBMS puts financial burden on the organization?29. DBMS represents a single point of failure for the entire system. What it means?30. Scaling a DBMS can be difficult. Why?31. What is meant by Vendor Lock-in?32. When we should not use DBMS system?Why DBMS is essential for an organization?

15 Jul, 2025 00:00:03 AM

The Complete Wordpress Course (No Coding), Domain Not NeededAre you ready to unlock the potential of WordPress and create stunning websites without the hassle of coding? Look no further! This comprehensive WordPress course is designed to empower you with all the essential skills you need to build your own website effortlessly. Whether you're a business owner, blogger, or simply looking to establish your online presence, this course is tailored to cater to your needs.What You'll Learn:1. Mastering Essential Plugins: Discover the power of WordPress through hands-on experience with over 10 popular plugins. From enhancing your website's functionality to improving user engagement, these plugins will become valuable tools in your website-building journey.2. Exploring Editor and Theme Builder Plugins: Unleash your creativity with three top-notch editor and theme builder plugins. Customize your website's appearance and layout without any coding skills, and watch your vision come to life with just a few clicks.3. Building SEO-Friendly Sites: A beautiful website is only effective when it's easily discoverable. Learn the art of Search Engine Optimization (SEO) and ensure your website ranks high on search engine results. Drive organic traffic and increase your website's visibility with proven SEO techniques.4. Beyond the Basics (The course is designed keeping the Pain Points of a WordPress Beginner in mind): This course goes beyond the fundamentals, equipping you with advanced techniques to make your website stand out. Learn about effective content strategies, responsive design, and user experience optimization to create a seamless browsing experience for your visitors.Why Choose Our Course:- No Prerequisites: This course is designed for beginners and doesn't require any prior experience in web development or design. We'll guide you through every step in a beginner-friendly manner.- No Domain or Hosting Plan Needed: Worried about purchasing a domain or hosting plan? Don't be! You can build and perfect your WordPress site directly on your computer. This eliminates any upfront costs and allows you to experiment and learn at your own pace.- Expert Guidance: If you encounter any challenges or have questions, I am just a message away.- Practical Hands-On Learning: Theory is important, but practical application is where the real learning happens. That's why our course is packed with hands-on exercises and real-time projects. You'll be actively building and refining your website as you progress.- Lifelong Skills: WordPress is a skill that will serve you for years to come. Whether you're managing your own website or helping others establish their online presence, the knowledge you gain from this course will be invaluable.Enrol now and embark on a WordPress journey that will empower you to create professional websites, boost your online presence, and bring your digital ideas to life – all without the need for coding skills or a domain!Enrol today and take the first step towards becoming a WordPress maestro. Your website-building adventure awaits!

15 Jul, 2025 00:00:03 AM

Welcome to the comprehensive guide to mastering Numerical Python, also known as Numpy. In this course, we dive deep into the Numpy library within the Python Programming Language, offering real-time coding exercises in Jupyter Notebook. Our aim is to demystify Numpy's functionality and empower you with the ability to leverage its power for efficient numerical computations.Numpy arrays are the cornerstone of numerical computing in Python. They provide a high-performance alternative to Python's built-in lists and tuples, enabling lightning-fast mathematical operations. Throughout this course, you'll explore a plethora of Numpy commands, equipping you with the skills to tackle a wide range of numerical tasks effortlessly.Let's embark on this journey to unlock the full potential of Numpy and revolutionize your approach to numerical computations. Whether you're a beginner or an experienced Python programmer, this course offers valuable insights and practical exercises to elevate your proficiency in numerical computing.Some Numpy Commands that we will use in this course.1. Import numpy as np2. 1-D Array - A = np.array( [1,2,3,4,5] ) # To create a One-dimensional array.3. 2-D Array - A = np.array( [[1,2,3],[4,5,6]] ) # To create a Two-dimensional array.4. 3-D Array - A = np.array( [[[1,2,3],[4,5,6],[7,8,9]]] ) # To create a Three-dimensional array.5. Array From List - L = np.array( [1,2,3,4,5] ) # To create an array from list.6. Array From Tuple - T = np.array( (11,22,33,44,55) ) # To create an array from tuple.7. np.asarray( ) - To convert any datatype (list,tuple) into numpy array.Ex : L_Array = np.asarray(list) ; T_Array = np.asarray(tuple)8. Dynamic Array - A dynamic array is similar to an array, but with the difference that its size can be dynamically modified at runtime.9. np.array( [1,2,3,4] , ndmin = 2 , dtype = complex ) # We can set the dimension and datatype of any array.10. np.arange() - A = np.arange( 1,20,3 ) # To create sequences of numbers.11. Reshape () - A = A.reshape ( 3,4 ) # To reshape an array.12. Ndim - A.ndim # To show the number of axis (dimensions/rank) of the array.13. shape - A.shape # Shape of the array i.e., matrix, rows, columns.14. Size - A.size # It shows the total no. of elements of the array.15. dtype - A.dtype # It shows the data type of elements of the array.16. itemsize - A.itemsize # It shows the size in bytes of each element of the array.17. type() - type(A) # It shows the type of the array.18. .data - # It indicates the memory address of the first byte in the array.19. strides - A.strides # It is the no. of bytes that should be skipped in memory to go to the next element.20. A = np.array( [[1,2,3], [4,5,6]] , dtype = float ) # Creating an array from lists with type float.21. Arrays Operations - A = np.array([1,2,3,4]) , B = np.array([11,22,33,44])A + B à [ 12 24 36 48 ] ;; B – A à [ 10 20 30 40 ] ;; A * B à [ 11 44 99 176 ] ;; B / A à [ 11. 11. 11. 11. ] , OR ,np.add(A,B) à [ 12 24 36 48 ] ;; np.subtract(B,A) à [ 10 20 30 40 ] ;; np.multiply(A,B) à [ 11 44 99 176 ] ;; np.divide(B,A) à [ 11. 11. 11. 11. ]22. Zeros Array - An array in which all values are 0- ZA = np.zeros( (3,4) , dtype = int/float/str ) # Creating an array of all zeros values of given shape and type.- We can define the shape and data-type of zeros array.- We can create 1-D, 2-D, as well 3-D zeros array.- The default data-type is float.23. Ones Array - An array in which all values are 1- A = np.ones( (4,3) , dtype = int/float/str ) # Creating an array of all ones values of given shape and type.- We can define the shape and data-type of ones array.- We can create 1-D, 2-D, as well 3-D ones array.- The default data-type is float.24. Full Value Array - An array in which all values are same (constant)- A = np.full ( (3,4), 7 ) # Creating an array of 3x4 with one constant value (7) everywhere.- We can define the shape, and pass the value to be filled in the 'Full Arrays'.- We can create 1-D, 2-D, as well as 3-D Full Array, with integer, float or string values.- The default data-type is Integer.25. Random module - This module contains the functions which are used for generating random numbers.A. Random Function - It returns random float number(s) between 0 and 1.np.random.random((2,3)) # It creates a 2-D array of shape 2x3 with random values.B. Randint Function- It generates random integer number(s) between given range.- By default, the range starts from 0.- The numbers can repeat.np.random.randint(5,20,4) # It create a 1-D array of given no. of integer values (4 here) between given input numbers 5 & 20. The values can repeat.np.random.randint(5,20,(4,3)) # It creates a 2-D array of shape 4x3, between given input numbers 5 & 20. The values can repeat.C. Rand Function - It returns random float number(s) between 0 and 1.np.random.rand(10) # It creates an array of 10 random numbers between 0 and 1.D. Randn Function - It returns random float numbers (positive and negative both) in the form of array.np.random.randn(2,3,4) # It displays values (+/-) in the form of arrays.E. Uniform Function- It returns random float number(s) between the given range of values.- The random numbers can't repeat.- By default, the range starts from 0.- If nothing is passed in (), it will return a float number between 0 and 1.np.random.uniform(1,5,50) # It displays given no. of unique values between given input numbers. The values can’t repeat. The values are in float format.F. Choice Function- It returns random integer number(s) from the given sequence.- The range starts from 0 by default.- If only 1 element is passed, then it will return a number between 0 and that element.- By default, replace = True , which means the numbers can repeat.np.random.choice( [2,5,8,9,1,7] , size=16 , replace=True/False) # To create an array with 16 elements from the given list of numbers ; replace = True means elements can repeatnp.random.normal( loc=100, scale=5 , size=10 ) # It draws a random sample from normal distribution ;loc – mean of distribution ; scale -std dev of distribution ; size – no. of elements.26. Linspace Function - np.linspace() - It returns evenly(linearly) spaced values within a given interval.np.linspace(start, stop , num=50, endpoint=True, retstep=True, dtype=None) ;Ex – A = np.linspace(2, 20, num=15) ; B = np.linspace (1,100,12)27. Flatten Array - A.flatten() # It is used to get a copy of array collapsed into 1-D.28. Empty Function - np.empty() - # Empty Function is used to create an array of arbitrary values, of given shape and datatype, without initializing the entries.A = np.empty( 4 ) ;; B = np.empty( (5,3) , dtype=int ) ;; C = np.empty( [2,5,3] , dtype=object )Syntax : np.empty ( shape, dtype )- Shape can given in list or tuple form- The default datatype is float29. We can define the data types of rows & columnsA = np.full( (2,3), 3, dtype = [ (‘x’,float) , (‘y’,int) ])30. Eye Function – np.eye() - The Eye Function returns a 2-D array , with 1 on diagonal and 0 elsewhere.Syntax : np.eye(shape, k, dtype)- Here, if only No. of Rows is passed, then No. of Columns = No. of Rows- K is Index of diagonal, by default, k=0 means Main diagonal ; when k=positive means Upper diagonal ; when k=negative means Lower diagonal- The default datatype is float31. Identity Array - np.identity() - It returns an identity array i.e., a square array with 1 on the main diagonal and all other elements are 0.Syntax : np.identity(shape, dtype)- It takes a single integer value only as shape.- The No. of Rows and No. of Columns will be equal to the given integer value.- The default datatype is float32. Ones Like Array - It returns an array of Ones, with the same shape & type as of the given array.Syntax : np.ones_like(array, dtype)Ex : A = np.ones_like(B) - It will return an array A of Ones, of same shape & type as of the given already created array B.33. Zeros Like Array - It returns an array of Zeros, with the same shape & type as of the given array.Syntax : np.zeros_like(array, dtype)Ex : P = np.zeros_like(Q) - It will return an array P of Zeros, of same shape & type as of the given already created array Q.34. Full Like Array - It returns a full array of Constant element, with the same shape & type as of the given array.Syntax : np.full_like(array, fill_value, dtype)Ex : X = np.full_like(Y, 7) - It will return an array X filled with constant value 7, of same shape & type as of the given already created array Y.35. Diagonal Function - It is used to extract the diagonal elements of an array, or , used to construct a new diagonal array.Syntax : np.diag(a, k)- If 'a' is a 2-D array, it extracts the diagonal elements.- If 'a' is a 1-D array, it constructs a 2-D array with elements of 'a' on diagonal.- By default, k is 0. Use k>0 for diagonals above the main diagonal. Use k<0 for diagonals below the main diagonal.36. Transpose Function - It converts the Rows into Columns, and Columns into Rows.Syntax : array.T , or , np.transpose(array)37. copy() - A = a.copy() # It returns a copy of the array.38. Operators - +, - , * , / - A = np.array([1,2,3]) ; B = A + 1 à B = [2,3,4] ; C = A * 2 à C = [2,4,6]39. Transpose - a.T # Coverts the rows into columns and columns into rows.40. Unary Operators - Those operators that require only one operand. Suppose ‘a’ is an array :a.max() , a.max(axis=1), a.max(axis=0) , a.sum()a.min() , a.min(axis=1) , a.min(axis=0) , np.sum(a, axis=1)# These functions can be applied row-wise or column-wise by setting an axis parameter.41. stack - c = np.stack( (a,b) ) # It creates a matrix using the arrays as rows.42. column_stack - c = np.column_stack( (a,b) ) # It creates a matrix using the arrays as columns.43. V-Stack and H-Stack - Vstack or Hstack is used to combine two or more arrays to form a new array.43.A) vstack - c = np.vstack( (a,b) ) # It appends the data vertically. a and b are arrays.43.B) hstack - c = np.hstack( (a,b) ) # It appends the data horizontally. a and b are arrays.44. Array Indexing - Indexing is used to obtain particular element(s) or row(s) or column(s) from the numpy array(s).Here, we pass the Index of the element to access it. The Index starts from 0, not from 1. It returns elements till "stop index - 1" index.Indexing in 1-D Array : Format - array[start index : stop index]Indexing in 2-D Array : Format - array[row_indexing, column_indexing]Indexing in 3-D Array : Format - array[matrix_indexing, row_indexing, column_indexing]Ex - a[1:2,1:2,1:2] # Since arrays may be multidimensional, we must specify a slice for each dimension of the array.45. Mix-Integer Indexing - a[1,1:2,1:2] # Mix integer indexing with Slice Indexing yields an array of lower rank. While, using only slices, it yields an array of same rank as the original array.46. Integer Array Indexing - a[[0,1,2],[0,1,0]] # It allows us to construct arbitrary (random choice) array using the data from another array.47. Boolean Array Indexing - a[a>2] # It is used to select the elements of an array that satisfy some condition.48. .dot() # It is used to compute inner product of the vectors, to multiply a vector by matrix, & to multiply matrixes.49. np.any(x > 0.9) # It checks if any value is greater than 0.9 in x. ( x = np.random.random(10))50. np.all(x >= 0.9) # It checks if all values are greater than or equal to 0.1 in x. ( x = np.random.random(10))51. array_A[array_A == x] = y # Replacing all x in the given array_A with y.52. a[[2,4]] or a[(1,3),:] # Getting the values from 2nd and 4th row of the matrix.53. To get the results from the matrix : a.sum(), a.std(), a.var(), a.mean(), a.max(), a.min()

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Python is a popular general-purpose programming language used for both large and small-scale applications. With Python, you can discover how to bridge web development and data analytics.The Python programming language is often the best choice for introductory courses in data science and machine learning. If you've been wondering how to learn python online to advance your career, you've come to the right destination.About UsLearntoupgrade is an online education platform providing rigorous industry-relevant programs designed and delivered in collaboration with world-class faculty and industry. Merging the latest technology, pedagogy, and services, Learntoupgrade is creating an immersive learning experience and getting you ready for the industry by empowering you with the latest skills and technology. We aim to bridge the gap between students and industry by helping students with the virtual training classes,Empower yourself for the Industry with usLearn to Upgrade is an online education platform providing rigorous industry-relevant programs designed and delivered in collaboration with world-class faculty and industry.Learn From AnywhereTake classes on the go with the Learntoupgrade app. Stream or download to watch on the plane, the subway, or wherever you learn best.A free certificate will be awarded to paid courses only.Enroll yourself and start learning...!Python Developer Salary, Python Jobs, Salary InformationMultinational tech companies are continuously looking for professionals skilled in the Python programming language, and this is pushing searches for Python jobs; salary-related searches are also getting pushed to the top of popular job portals. The roles of a Python developer vary from Data Scientists to Application Developers, Sys Admins to DevOps Engineers, and Web Developers. The following is the average Python developer salary for these different roles:Data Scientist: 78,456 USD/yearDevOps Engineer: 97,310 USD/yearSoftware Developer: 110,305 USD/yearSenior Software Engineer: 90,596 USD/yearSoftware Engineer: 90,662 USD/yearEntry-Level Python Developer SalaryThe average entry-level Python developer salary is 59,888 USD/year to 111,605 USD/year.Junior Python Developer SalaryThe average junior Python developer salary, which may also be classified as mid-level, is 117,940 USD/year.Senior Python Developer SalaryThe average senior Python developer salary is 132,789 USD/year to 145,923 USD/year.Python Developer Salary in the USAs a Python developer, you can expect to earn a good salary in the United States. But your exact salary will depend on a number of factors, including your experience, location, and the specific company you work for.However, salaries will vary depending on the city you live in. For example, Python developers in San Francisco can expect to earn significantly more than those in other parts of the country.And experience also plays a major role in the python developer's salary. If you have several years of experience under your belt, you can expect to earn a higher salary than someone just starting.Similarly, if you have specialized skills or knowledge, you may be able to command a higher salary as well.In general, Python developers in the US can expect to earn an average salary of around $96,000 per year.So, what is the average Python developer salary in the United States? Here is a breakdown of salaries by city:San Francisco: $143,476California: $138,466New York: $132,598Los Angeles: $105,000Boston: $100,000Chicago: $95,000Houston: $90,000Dallas: $85,000Atlanta: $80,000Seattle: $75,000As you can see, there is a wide range of salaries for Python developers in the US.Python Developer Salary in IndiaPython developers are in high demand in India, and their salaries reflect that. In general, Python developers can expect to earn salaries in the range of ₹4,00,000 to ₹8,00,000 per year, but they are depending upon their experience and skills.Bangalore and Hyderabad are two of the best-paying cities for Python developers, with salaries in the range of ₹6,00,000 to ₹8,00,000 per year.Chennai and Pune are also good options, and you can get as a python developer around ₹4,00,000 to ₹6,00,000 per year.Delhi, Mumbai, and Kolkata are also good options for Python developers, and the salary range should be between ₹4,00,000 to ₹6,00,000 per year.

15 Jul, 2025 00:00:03 AM

Overview:Welcome to the Data Science Learning Course, your gateway to the fascinating world of data-driven decision-making and analytics. In today's digital age, data is the currency that drives industries and innovation. Our comprehensive program is designed to equip you with the knowledge and skills needed to harness the power of data science. Whether you are a novice or a seasoned professional looking to upskill, our course will provide you with a solid foundation in this dynamic field.Benefits of Learning Data Science:Unlock Career Opportunities: Data science is in high demand across various industries. By mastering data science, you open doors to exciting and well-paying career opportunities.Solve Real-World Problems: Gain the ability to extract valuable insights from data, helping organizations make informed decisions and solve complex challenges.High Earning Potential: Data scientists are among the highest-paid professionals. Learn how to command competitive salaries and enjoy financial stability.Innovation and Automation: Be at the forefront of technological innovation, as data science drives automation, machine learning, and AI advancements.Global Relevance: Data science skills are sought after worldwide, providing you with the flexibility to work in India or abroad.Who Can Learn:Our Data Science Learning Course is suitable for:Students: Kickstart your career with a strong foundation in data science.Professionals: Enhance your skill set and stay relevant in a rapidly evolving job market.Entrepreneurs: Leverage data to make data-driven decisions and gain a competitive edge.Career Changers: Switch to a rewarding career in data science regardless of your background.Career Scope:Data science offers an extensive range of career opportunities, including but not limited to:Data Scientist: Analyze data to extract actionable insights.Machine Learning Engineer: Develop algorithms and models.Data Analyst: Interpret data and create reports.Business Analyst: Help organizations make data-driven decisions.Big Data Engineer: Manage and process vast datasets.AI Researcher: Pioneer cutting-edge AI solutions.Salary Package (India and Foreign):In India, data science professionals can earn competitive salaries based on experience and expertise. Entry-level positions often start at 5-10 lakhs per annum, while experienced data scientists can command salaries exceeding 20 lakhs per annum. In foreign countries, such as the United States, data scientists can earn even more, with salaries ranging from $80,000 to 150,000 per year, depending on location and experience.Requirements To Study:To enroll in our Data Science Learning Course, you'll need:A basic understanding of mathematics and statistics.Familiarity with programming languages like Python.A laptop or computer with internet access.Dedication and a passion for learning.

15 Jul, 2025 00:00:03 AM

OverviewPython is a general-purpose programming language that is used for a wide variety of tasks, including:· Web development· Data science· Machine learning· Software development· System administration· Scientific computing· ScriptingPython is a high-level language, which means that it is closer to human language than to machine language. This makes it easier to read and write Python code, and it also makes it more portable, meaning that Python code can be run on different platforms without having to be recompiled.Python is also an interpreted language, which means that the code is executed line by line by the Python interpreter. This makes Python programs faster to develop, as there is no need to compile the code before it can be run.Python is a dynamically typed language, which means that the type of a variable is not known until it is assigned a value. This can make Python code more flexible, but it can also make it more difficult to debug.Python is a very popular programming language, and it is used by a wide variety of people, from beginners to experienced developers. Python is also a very well-documented language, so there are many resources available to help you learn Python.Benefits of Learning· Easy to learn and use· Portable· Powerful· Versatile· Well-documented· Active communityIf you are looking for a general-purpose programming language that is easy to learn and use, then Python is a great choice. Python is also a powerful language that can be used for a wide variety of tasks.Here are some of the things that Python is used for:· Web development· Data science· Machine learning· Software development· System administration· Scientific computing· ScriptingIf you are interested in learning more about Python, there are many resources available online. You can also find many Python books and tutorials at your local library or bookstore.Who can learn?Python is a general-purpose programming language that can be learned by anyone, regardless of their age, education, or experience. However, there are some people who may be more likely to succeed in learning Python than others. These people include:· People with a logical mind. Python is a very logical language, so people who are good at thinking logically will be more likely to succeed in learning it.· People who are good at problem-solving. Python is a very powerful language, but it can also be very complex. People who are good at problem-solving will be more likely to be able to overcome the challenges of learning Python.· People who are persistent. Learning any new language takes time and effort. People who are persistent and willing to put in the work will be more likely to succeed in learning Python.Of course, even if you don't fit into any of these categories, you can still learn Python. With hard work and dedication, anyone can learn to program in Python.Here are some additional tips for learning Python:· Start with the basics. Don't try to learn everything about Python all at once. Start with the basics, such as variables, data types, and control flow. Once you have a good understanding of the basics, you can start learning more advanced concepts.· Find a good learning resource. There are many different resources available to help you learn Python. Books, tutorials, and online courses can all be helpful.· Practice regularly. The best way to learn Python is to practice regularly. Try to write some code every day, even if it's just a small program.· Don't be afraid to ask for help. If you get stuck, don't be afraid to ask for help. There are many online forums and chat rooms where you can get help from other Python programmers.What are the salary package specially in all over the world?Country                           Average Salary (USD)United States                 $102,333Switzerland                     $103,596United Kingdom             £55,000Canada                             $67,425Germany                          €69,292Netherlands                    €65,000Australia                           AUD90,000India                                  ₹4,50,000Brazil                                 R$120,000China                                 ¥120,000These are just averages, and the actual salary you earn will depend on your individual circumstances. However, these numbers give you a good idea of the salary range for Python developers in different countries.As you can see, the average salary for Python developers is highest in the United States and Switzerland. These countries are also home to some of the largest tech companies in the world, which means there is a high demand for skilled Python developers.The salary range for Python developers is also quite wide. In some countries, entry-level Python developers can earn as little as $50,000 per year, while experienced developers can earn over $200,000 per year.If you are interested in becoming a Python developer, it is important to research the salary range in your desired location. This will help you set realistic expectations and make sure you are compensated fairly for your skills.Key Features of Python:· Easy to learn and use. Python is a very readable language, and it has a simple syntax. This makes it easy for beginners to learn, and it also makes it a good language for experienced developers who want to write concise and efficient code.· Portable. Python code can be run on many different platforms, including Windows, macOS, Linux, and Raspberry Pi. This makes it a good language for developing applications that need to be portable.· Powerful. Python is a very powerful language, and it can be used to develop a wide variety of applications. This includes web applications, data science applications, and machine learning applications.· Versatile. Python can be used for a wide variety of tasks, including scripting, system administration, and scientific computing. This makes it a very versatile language.· Well-documented. Python has a very well-documented language, and there are many resources available to help you learn Python. This makes it easy to find help when you need it.· Active community. Python has a very active community, and there are many people who are willing to help you learn Python. This makes it a great language for beginners who want to get help from experienced developers.These are just some of the key features of Python. If you are looking for a general-purpose programming language that is easy to learn, powerful, and versatile, then Python is a great choice.Some additional features of Python:· Object-oriented programming. Python supports object-oriented programming, which is a powerful way to organize code.· Automatic memory management. Python has automatic memory management, which means that you don't need to worry about manually allocating and freeing memory.· Large standard library. Python has a large standard library, which includes many useful functions and modules.· Extensible. Python is extensible, which means that you can add new features to the language.· Embeddable. Python can be embedded in other applications, such as web browsers and games.

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WHY PHPPHP is used in more than 70 percent of the websites across the Internet. That’s HUGE!PHP is more alive than ever! It’s simple yet very powerful. It’s secure. It’s scalable.It’s very easy to learn.Just to get an idea of how powerful PHP is, Websites like Facebook, Wikipedia, Slack, MailChimp, Flickr, SourceForge, Tumblr, Etsy and Yahoo have PHP as their core.oh and not to forget, the biggest blogging system on the web (WordPress), is powered by PHP.enough teasing let’s get started with PHP.In this course:You will learn the Basics (installation, variables, data types, conditionals, and more ... )You will get more skilled by learning about functions, cookies, sessions, database, object oriented programming and more ...You will learn more advanced Topics like dependency management, security, testing, creating packages, MVC frameworks and more ...You will do more than 12 projects / exercises to put your knowledge in practiceand a lot moreYou don’t need any programming experience. You will learn everything you need to know, right here!This Course is for:Beginners to programmingDevelopers who want to learn PHPCurious to learn Back-end developmentPHP Developers who want to improve their skillsAnyone who wants to start their path to web developmentIf this is you, then what are you waiting for?! Let’s get Started

15 Jul, 2025 00:00:03 AM

**Everything there is to know about JavaScript gift-wrapped in a single comprehensive course**JavaScript is the most popular programming language in the world. It powers the entire modern web. It provides millions of high-paying jobs across the globe. That's why you want to learn JavaScript too.Whether you want a career in front-end or back-end development - you must have a solid understanding of this universal language!And you came to the right place!Why Choose This Course?This course is a must-attend for four no-brainer reasons:• Comprehensive JavaScript Course: It's an all-in-one package that will take you from the very fundamentals of JavaScript to building modern and complex applications.• Modern JavaScript Made Easy: You’ll receive guidance through practical and fun code examples, critical theories about how JavaScript works behind the scenes, and beautiful and complete projects.• Think like a developer: You’ll learn how to plan application features, architect your code, debug code, and a lot of other real-world skills that you will need in your developer job.• From Beginner to Expert: Unlike other courses, this one contains beginner, intermediate, advanced, and even expert topics, so you don't have to buy any other course to master JavaScript from the ground up!It is a fundamentals course that’s great for both beginners and experts alike. If you’re on the lookout for a course that starts from the basics and works up to the advanced topics, this is the best course for you.It only teaches what you need to get started with JavaScript with no fluff. While this helps to keep the course pretty concise, it’s about everything you need to get started with the topic.

15 Jul, 2025 00:00:03 AM

React JS has taken centre stage in easing the creation of dynamic user interfaces and websites and apps as the relevance of creative and interactive UIs grows. Because JavaScript is one of the most widely used languages for websites and apps, it's no wonder that many people are working on libraries and frameworks to help it grow. And one of the most popular is React, which allows you to create unique HTML components and create sophisticated apps in a short amount of time.However, these frameworks and libraries are not always simple to understand, so we created this course. This course breaks down challenging ideas, making them easier to comprehend even for newcomers to the development field.The course is enjoyable, engaging, and interactive, which means it does not consist of introductory lectures that go over your head but rather a more hands-on approach to the subject. The material is kept light and enjoyable by the clever and experienced educator. Essential learning tools such as quizzes and assignments are also included in the lesson to assist you in gaining a better understanding of the subject.So What Exactly Is Covered in The Course?· An overview of React and its fundamental ideas· Discover what JSX is, how it works behind the scenes, and when to employ stateful and stateless components.· Working with function and class-based components· Importing and exporting React Modules· Understanding how the render method works in detail· React component lifecycle and multiple lifecycle methods.· Using reusable components to create dynamic websites· Creating an excellent operating structure for a project from the ground up will aid in its long-term maintenance.What are You Waiting for? Become a top React developer today!This course will push and challenge you to progress from being a complete novice in React to being among the top 10% of React developers.It is, without a doubt, a complete online React JS course you won't find anywhere else. This comprehensive guide will walk you through fundamental, intermediate, and advanced React JS subjects. You'll also be working on various projects while learning all the skills needed to become a top React developer.You don't need any previous knowledge of React or any other JS framework to get started. However, to complete this course, you need a basic understanding of HTML, CSS, JavaScript.

15 Jul, 2025 00:00:03 AM

Python is famed as one of the best programming languages for its flexibility. It works in almost all fields, from web development to developing financial applications. However, it's no secret that Python’s best application is in deep learning and artificial intelligence tasks.While Python makes deep learning easy, it will still be quite frustrating for someone with no knowledge of how machine learning works in the first place.If you know the basics of Python and you have a drive for deep learning, this course is designed for you. This course will help you learn how to create programs that take data input and automate feature extraction, simplifying real-world tasks for humans.There are hundreds of machine learning resources available on the internet. However, you're at risk of learning unnecessary lessons if you don't filter what you learn. While creating this course, we've helped with filtering to isolate the essential basics you'll need in your deep learning journey.It is a fundamentals course that’s great for both beginners and experts alike. If you’re on the lookout for a course that starts from the basics and works up to the advanced topics, this is the best course for you.It only teaches what you need to get started in deep learning with no fluff. While this helps to keep the course pretty concise, it’s about everything you need to get started with the topic.