Artificial Intelligence vs. Machine Learning vs. Data Science
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Artificial Intelligence vs. Machine Learning vs. Data Science

Today, many organizations are focused on Artificial intelligence, machine learning, and data science to gain the maximum value for every asset by developing advanced applications and expert systems. As process automation is regarded as an integral part of today’s business operation, data science, artificial intelligence, and machine learning have been topics of talk in recent years. Although all three terms are reciprocally connected, each term has different functions and roles. However, many confuse Artificial intelligence vs. machine learning vs. data science as they find it tough to separate them. This is why we are here to eliminate misconceptions regarding the terms. So, keep on reading to grasp artificial intelligence vs. machine learning vs. data science.  

What is Artificial Intelligence? 

Artificial Intelligence commonly known as AI is the process in which machines simulate human intelligence. In simple words, Artificial Intelligence means programming a machine to mimic human behavior and mentality. However, when people hear about “Artificial Intelligence”, most imagine robots, which is a wrong concept. AI is much more than just an automated machine that performs physical activities as they are built to assist people by performing complicated learning and problem-solving activities by replicating human cognitive behavior.  

Machine Learning, a subset of AI, is the process of developing intelligence within a computer system. So, it is not surprising that many people easily confuse machine learning vs. AI though they are different.  

For a clear understanding of Machine learning vs. AI, let’s take an example of modern Transportation Application technology. Today, we have an automated vehicle that offers the feature of “auto-drive” which is an example of Artificial Intelligence as it automatically drives the vehicle without the complete involvement of humans. On the other hand, the same transportation application uses machine learning for traffic forecasting by combining historical trends and current data.

Scope of Artificial Intelligence in Nepal 

Recently, also in Nepal, Artificial Intelligence applications skyrocketed in terms of popularity as we can see their wide use in different industrial sectors.

Wonder about the uses of artificial intelligence in Nepal? Well, let’s go through some examples. Today, there are growing numbers of restaurants in Nepal that are following innovative ways to serve the people with the use of modern robots for unique experiences. Likewise, different banks started using chat assistants on their websites for linking transactions and assuring compliance. Besides, we can also see the implication of Artificial intelligence in other areas including important sectors such as transportation, and health care which shows the growing demand for Artificial Intelligence in NepalSo, it will not be wrong to say there is an enormous scope of artificial intelligence in Nepal, despite the country being under the tag of a developing country.

 After studying Artificial Intelligence in Nepal, you can commence your career with the job positions listed down.

  • Technology Consultant
  • Business Intelligence Developer
  • Artificial Intelligence Specialist
  • Robotics Engineer
  • Computer Vision Engineer
  • Artificial Intelligence  Analyst

Artificial Intelligence Skills 

Now, we know there are tremendous opportunities for the fields of Artificial Intelligence in Nepal, however, only professionals with the right skills succeed to live fulfilling careers. So, if you are looking to kick start your dream career in this field, firstly, make sure to become proficient in the Artificial Intelligence skills listed below. 

  • Programming languages such as C / C++, Python, MATLAB, JavaScript, Java, and Julia.
  • Data Engineering.
  • Machine learning security solutions.
  • Analytical skills. 
  • Neural Networks
  • Autonomous Driving.
  • Exploratory Data Analysis
  • Communication Skill
  • Leadership skill
  • Critical-thinking skill

What is Machine Learning? 

Machine Learning is a subdivision of AI, where a computer system utilizes data and algorithms to simulate human learning behavior to make predictions. The concept is very similar to the way the human mentality works. The difference is that people obtain the knowledge and information for making a decision whereas the computer system depends on the input data and information to forecast predictions.  

The prime purpose of machine learning is to master the computer system to show the result autonomously without much intercession from humans. The machine studies the input data to find out the patterns and adjust the results based on the previous examples. 

Scope of Machine Learning in Nepal 

Machine learning is a fast-growing field in the world that identifies the data pattern and its algorithms in the system to predict future results. In Nepal too, many organizations are seen using machine learning for different operational activities such as data mining, bank card fraud identification, robotics, biometrics, and studying the stock markets. The growing popularity skyrocketed the demands and opportunities for skilled professionals resulting in the enormous scope of machine learning in Nepal.  

After studying Machine Learning in Nepal, you can begin your career with the job positions listed down.

  • Machine Learning Engineer
  • Robotics Engineer
  • Data Mining
  • Data Analysis
  • Computational Linguist
  • Business Intelligence Developer

Machine Learning Skills 

Machine learning in Nepal is a rewarding career with handsome pay. However, machine learning is a highly demanding job, so you are required to be highly skilled for fulfilling the role and responsibilities. Here are some of the key Machine Learning Skills to learn before diving into the field. 

  • Statistics and Probability 
  • Data modeling skills
  • Software Engineering skills
  • Machine Learning Algorithms
  • Neural Networking
  • Computer languages such as C / C++, Python, MATLAB, JavaScript, Java, Julia
  • Applied Mathematics

What is Data Science? 

Data science is a combination of machine learning and Artificial intelligence with different other elements including math and statistics to provide clear insights on the business data for decision making. 

When comparing Artificial intelligence vs. machine learning, many usually include data science as the topic of discussion. This is because data scientists relate the machine learning elements such as texts, numbers, and images for building AI which is used for generating a deep understanding of the data to assist in an organization’s strategic planning.

Scope of Data Science in Nepal 

Today, almost all organizations depend on a huge amount of data for planning future business operations. It is important that they interpret the data accurately for ensuring effective decision-making for the success of the organization. For this reason, most businesses place data scientists as an integral asset heightening the scope of data science in Nepal. 

After studying Artificial Intelligence in Nepal, you can commence your career with the job positions listed down.

  •  Data Analyst
  •  Data Scientist
  •  Database Administrator
  •  Business analyst
  • Analytics Manager

 Data Science Skills 

A data-driven professional with high technical as well as soft skills is required for gaining effective and efficient insights into data in any organization. So, what data science skills do you require for brilliant performance in the field? The key skills are listed down. 

  • Database and programming language skills such as C / C++, Python, MATLAB, JavaScript, and Java 
  • Statistical analysis skill
  • Web scraping
  • Machine learning skill
  • Big data skill
  • Cloud Computing Skill
  • Data visualization skill 

AI vs. Machine Learning 

As discussed earlier, Artificial Intelligence and Machine learning are closely interrelated but are different when it comes to functionality. Where Artificial Intelligence is all about building a smart system for solving complicated challenges imitating the human brain, Machine learning deals with the input data and algorithms for forecasting accurate results.  

Depending on its historical data, machine learning works with structured and semi-structured data to generate meaningful outcomes. Let’s note that machine learning can perform on just one particular domain for which we have created the model. For instance, if we have built a model for identifying the picture of cars, it will only be responsive when we inquire about cars, else if we search for other vehicles like motorbikes, it won’t show any results. On the other hand, Artificial intelligence is built to be smarter as it works well with structured, semi-structured as well as unstructured data for simulating human behavior. Plus, AI has a wide range of scopes when we compare AI vs. Machine Learning. 

Data science vs. Machine Learning 

Despite data science and machine learning both depending on the analysis of data, they are not the same in the way they work. Data science works by collecting, processing, and studying large data for creating insights. On the opposite side, machine learning learns from historical data patterns to accurately predict the result. 

Data science is more complex as it handles the unstructured raw data whereas machine learning utilizes significant mathematical and algorithm concepts. Plus, data science gets the input data mostly from human-consumable types, unlike machine learning which gets the data in a form that can be used as algorithms. 

Data science vs. Artificial Intelligence 

As discussed above, data science is all about collecting, processing, and studying large data for creating insights and finding hidden patterns in data to aid in making crucial decisions in the organization. On the other side, Artificial intelligence is built with features for handling the data autonomously to perform like humans themselves. The main aim of data science is to develop complex models for extracting different facts whereas artificial intelligence aims to stimulate human cognitive behavior. 

Difference between Data Science, Artificial Intelligence, and Machine Learning

Data Science
Machine Learning
It creates insights into the data.
It performs tasks thinking like a human.
It uses the previous data records for analysis to forecast the results.
It contains different data operations.
It includes Machine Learning.
It is a subset of Artificial Intelligence.
Major Skills Required:
Advanced Math
Data visualization
Database Management
Modeling and Analytics
Major Skills Required:
Statics and Probability
Big data technology
Advanced Math
Major Skills Required:
Natural Language processing
Video and Audio processing
Neural Network Architecture
Major tools used:
Apache Spark
Major tools used:
Scikit Learn
Tensor Flow
Major tools used:
IBM Watson Studio
Amazon Lex2
Microsoft Azure ML Studio
Fraud Detection
Financial Analysis
Facial Recognition
Search algorithms


Are Machine Learning and Data Science the same? 

No Machine Learning and Data Science are not the same. Data Science aids to provide insights into data for understanding trends whereas Machine Learning studies historical data patterns to predict results. 

Is Data Science required for Machine Learning? 

Machine Learning and Data Science are closely related to each other. So, it is ideal to learn the basics for both to learn each. 

Can a Data Scientist become a Machine Learning Engineer? 

Yes, as a data scientist you can also work as a Machine Learning Engineer. As a Machine Learning Engineer has to be proficient in data science, mathematics, and computer programming as the key requirement, it won’t be difficult for a data scientist to change the career to Machine Learning Engineer. 

 Which is better, Machine Learning or Data Science? 

Well, it depends on your career choice. If you are looking for a career in business management, data science is better, however, if you are looking for a career as a machine learning engineer, then machine learning is better for you.

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