Computer Basic for Beginners
@. Computer:
Computer is an electronic device which is developed by Chars Babas nearby 14th century.
It receives input from input device and processing the input. Finally, it gives output. It also puts storage of data and information.
@. Computer part:
Computer has two parts – (1) Hardware (2) Software
@. Computer Hardware:
Hardware is a type of physical external and internal device of computer. We can see and touch them.
Hardware is two types: (1) Input device (2) Output device
#. Computer input device is keyboard, mouse, scanner, etc. and
#. Computer output device is monitor, printer, speaker, projector, etc.
@. Computer Software:
Software is a set of instructions, data, or programs used to operate computers and execute specific tasks.
Software is two types: (1) System Software (2) Application Software
#. System software is Windows, Mac OS, Linux,Chrome OS etc.
#. Application software is Ms Word, Photoshop, Chrome, Yahoo, etc.
@. Computer type:
There are several types of computer. Among them:
(1) Personal Computer (5) Server
(2) Workstation Computer (2) Mainframe
(3) Super Computer (2) Tablet
(4) Embedded Computer (2) IoT Device
#. Personal Computer or PC:
These are the most common type of computers used by individuals for personal tasks like browsing, word processing, gaming, etc.
Such as: Desktop and Laptop.
#. Workstation Computer:
Workstation computer is high-performance computers designed for professional tasks like video editing, 3D modeling, and scientific simulations.
#. Super Computer:
Super computer is the most powerful computers capable of performing massive calculations and simulations.
They are used for scientific research, weather forecasting, and complex simulations.
#. Embedded Computers:
Embedded Computer is built into other devices and performs specific tasks.
Such as: Microcontrollers in appliances, Cars, and Industrial machinery.
#. Server:
Server is a type of computer designed to serve other computer over a network.
They handle tasks like data storage, hosting websites, running applications, and managing network resources.
#. Mainframes:
Mainframe is large and powerful computers used by organizations for critical tasks like processing large volumes of data, financial transactions, and handling enterprise-level applications.
#. Tablet and Smart Phone:
Tablet is not only mobile device but also computer, with integrated processors and operating systems, used for various tasks, including communication, browsing, and entertainment.
#. IoT or Internet of Things Device:
IoT is a wide range of device connected to the internet to collect and exchange data.
Such as: Smart home device, Smart speaker, and Connected appliance.
@. Data: Computer input is called data.
@. Information:
The output obtained after processing data, based on the user’s instructions is called information.
@. Processes that can be applied to data are of two types:
- Arithmetic operations
- Logical operations
@. The basic parts of computer are:
#. Input unit: Devices used to input data and instructions.
#. Output unit: Devices used to provide information to the user in desired format.
#. Control unit: All devices or parts of computer interact through the control unit.
#. Arithmetic logic unit: All arithmetic operations and logical operations take place it.
#. Memory: All input data, instructions and data interim to the processes are stored in the memory.
@. Memory is of two types
- Primary memory
- Secondary memory.
#. Primary memory:
Computer primary memory, also known as RAM, is a fast and volatile storage that holds data and instructions for the CPU to access during program execution. It allows for efficient multitasking and smoother system performance.
#. Secondary memory:
Persistent storage (Hard disk, SSD, etc) for data retention when the computer is off.
@. CPU:
Control unit, arithmetic logic unit and memory are together called the central processing unit or CPU.
@. Speed:
Typically, a computer can carry out 3-4 million instructions per second.
@. Accuracy:
Computers exhibit a very high degree of accuracy. Errors that may occur are usually due to human errors.
@. Reliability:
Computers can carry out same type of work repeatedly without throwing up errors due to tiredness or boredom
@. Versatility:
Computers can carry out a wide range of work.
@. Storage Capacity:
Computers can store a very large amount of data at a fraction of cost of traditional storage of files
@. Internet:
Internet is a global network of connected computers that allows access to information and services.
@. Programming:
Programming is writing instructions or code for computers to perform specific tasks.
Some Advantages that Computers Offer.
#. Computers can do the same task repetitively with same accuracy.
#. Computers do not get tired or bored.
#. Computers can take up routine tasks while releasing human resource for more intelligent functions.
Some Disadvantages of Computers
#. Computers have no intelligence.
#. Regular electric supply is necessary to make computers work.
#. Trained people required to work on computers.
@. Artificial Intelligence or AI:
Artificial Intelligence or AI is the simulation of human intelligence in computers and active them to learn and make decisions.
@. Cyber Security:
Cyber Security is protecting computer systems and data from unauthorized access and attacks.
@. Block-Chain:
Block Chainis a decentralized and secure digital ledger used for recording transactions.
@. Cloud:
The “cloud” refers to using internet-based servers to store, manage, and process data, replacing the need for local computers or servers.
It offers benefits like scalability, cost-efficiency, and accessibility for various services and resources.
@. Machine Learning:
Machine learning is a subset of artificial intelligence (AI) that involves the development of algorithms and models that enable computers to learn from and make predictions or decisions based on data, without being explicitly programmed.
@. Machine learning can be categorized into three main types based on the learning process and the nature of the data used for training:
- Supervised Learning:
In supervised learning, the algorithm is trained on a labeled dataset, where the input data is paired with the correct output.
The goal is for the algorithm to learn a mapping from inputs to outputs, so that it can make accurate predictions or classifications when presented with new, unseen data.
- Unsupervised Learning:
Unsupervised learning involves training the algorithm on an unlabeled dataset, where the algorithm’s goal is to identify patterns, structures, or relationships within the data.
Clustering and dimensionality reduction are common tasks in unsupervised learning.
- Reinforcement Learning:
In reinforcement learning, an agent learns to perform actions in an environment to maximize a reward signal.
The agent receives feedback in the form of rewards or penalties based on its actions, and it learns to make decisions that lead to higher rewards over time.
This type of learning is often used in scenarios where there is no explicit dataset of labeled examples.
@. Additionally, there are other variations and combinations of these types:
#. Semi-Supervised Learning:
This approach uses a combination of labeled and unlabeled data for training, which can be particularly useful when labeling large amounts of data is time-consuming or expensive.
#. Transfer Learning:
Transfer learning involves training a model on one task and then using that pre-trained model as a starting point for a different but related task.
This can save time and resources, as the model has already learned relevant features from the initial task.
#. Deep Learning:
Deep learning is a subfield of machine learning that focuses on using neural networks with many layers (deep neural networks) to automatically learn hierarchical representations of data.
Deep learning has been highly successful in tasks like image and speech recognition.
@. Each type of machine learning has its own strengths and is suited to different types of problems.
The choice of which type to use depends on the available data, the nature of the problem, and the desired outcomes.
@. Computer Vision:
Computer vision is a field of artificial intelligence that focuses on enabling computers to interpret, understand, and process visual information from the world, much like human vision.
It involves tasks such as image recognition, object detection, and scene understanding using algorithms and machine learning techniques.
@. A machine is a device or system designed to perform specific tasks, often using mechanical or electronic means.
#. A machine is a mechanical or electronic device designed to perform specific functions or tasks.
@. Simple Sum:
62 + 24 – 32 = 54
- Input ~ 62, 24, 32, +, -, =
- Output ~ 54
- Instructions ~ +, –
- Data ~ 62, 24, 32, 54
- Information ~ Processed data (54)
@. Data:
Computer input is called data.
@. Information:
After processing data, according to user instruction is called information.
@. Different between Data and Information:
| No | Data | No | Information |
| 01 | Computer input is called data. | 01 | After processing data, according to user instruction is called information. |
| 02 | Data has all the elements of analysis. | 02 | Information is dependent on data |
| 03 | Data is just number and text. | 03 | Information is based on analysis of data |
| 04 | Data does not have any specific purpose. | 04 | Information is always useful. |
| 05 | Such as: 7, 5, 9, 2, 1, 0, 3, 4, 6, 8 | 05 | Such as: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 |
@. Before a machine can follow instructions:
- It needs to store the numbers in a memory just like M of a calculator.
- Let’s therefore imagine that we have three memories like a calculator.
- M1, M2 and M3
@. Q-basic:
The machine dictionary we are going to use is called QBASIC.
@. How will a machine understand the instructions you are giving?
- It needs something like a dictionary.
- You also need to know the words that are in the dictionary.
- The dictionary we are going to use is called QBASIC.
@. The following commands which you can use to input into memory and output from memory:
- INPUT M1
- INPUT M2
- M3 = M1 + M2
- PRINT M3
@. Try the program out in the QBASIC dictionary.
- Find the folder lab Y MI
- It find QBASIC folder
- Find QB.exe
- Load QB
- Write and run program
- Change the formula, try again.
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