Artificial Intelligence and Data Science both are branches of computer science. The terms artificial intelligence (AI) and data science are often used interchangeably in the technological era, but they vary in numerous aspects. The primary difference between these two areas of study is that data science refers to the methods used to collect, process, and then make sense of vast amounts of data. At the same time, artificial intelligence refers to programming a computer with a body of knowledge so it can make predictions, often modelled after the human mind and its behaviour. The skillset required to be a Data Scientist includes Python, Statistics, Jupyter Notebook, TensorFlow, SQL, NLP etc. In contrast, the skills necessary to be an AI professional include Java, AI system, Python, C++, computer science, scala, Pytorch, spark etc. So, go through the complete blog to understand the difference, job description, skill sets and salary structure between Data Science and AI.
What are data science and artificial intelligence?
Data Science
Data science is the extraction of valuable insights from raw and unstructured data. It is one of the interdisciplinary ways that combine different fields of statistics, and scientific methods to draw results from raw data points.
Data science is believed to have brought about the fourth industrial revolution, and it is the core component in the decision-making of any business. Most companies are well aware of the value of data analysis and processing. Whether the business is small or large, they are capitalising on the importance of data science day by day. You can visit the official website of Board Infinity to avail of the Data Science Online Course with Placement.
The Data Science Lifecycle
● Capture: This includes Data Extraction, Data Entry, Data Acquisition, and Signal Reception. The various steps involve gathering raw structured and unstructured data.
● Maintain: It involves Data Cleansing, Data Warehousing, Data Processing, Data Staging, and Data Architecture. This step consists of collecting raw data and assembling them to make a proper structure of the database.
● Process: This involves Clustering/Classification, Data Mining, Data Summarization, and Data Modelling. The working profile of a data scientist consists of preparing and examining data, its range, patterns, and biases to calculate how it is helpful in the prediction of patterns and the analysis.
● Analyse: This step consists of Predictive Analysis, Exploratory or Confirmatory, Text Mining, Regression, and Qualitative Analysis.
● Communicate: The final step involves data visualisation, data reporting, decision-making, and business intelligence. Here, the analysts present their analyses in graphs, reports, and charts so that they are easily readable.
Artificial Intelligence
Artificial intelligence, or AI, combines complex algorithms designed to mimic human intelligence. AI-programmed computers can “learn” as they go, improving their ability to solve specific issues as they collect more data. Translations, picture recognition, interpreting human speech, speech recognition, and decision-making. AI is a human-made technology that allows machines to read, learn, and understand data to assist in decision-making. These actions are based on conclusions that are difficult to detect in humans. It has two categories in modern technology: general AI and applied AI.
The primary cognitive skills on which the AI programs focus are learning, reasoning, and self-correction.
● Learning processes: The learning perspective of the AI program focuses on creating rules and acquiring data. These rules are known as algorithms that provide stepwise guidelines for the computing devices to complete the provided task.
● Self-correction process: This function of the Artificial Intelligence program aims to tune the algorithms consistently to make sure that they create feasible results.
● Reasoning processes: The reasoning aspect of Artificial Intelligence programming focuses on picking the correct algorithm for the desired outcome
What difference between data science vs artificial intelligence, which is better?
As we have read above, data science is the branch that deals with the analysis of the data and processing and maintenance of the data. In contrast, AI deals with solving complex algorithms designed to reduce human efforts. So, if you have a good command of statistics, mathematics, and calculation, you might opt for data science as your career path. If you have a keen interest in programming, software, and algorithms, you might opt for AI. You might find Board Infinity’s AI & Machine Learning Course with Placement intriguing in this aspect.
Conclusion
Artificial Intelligence has yet to be fully explored, but Data Science has already significantly impacted the industry. Data Science puts data into a format that can be visualised and analysed. In the modern era, numerous new products are produced far better than their current form, and it provides autonomy by performing many tasks automatically. We have also read that with the help of data science, the data is analysed more accurately and visually. If you aspire to become a data scientist or specialist, we highly recommend checking out the Board Infinity Data Science online course.
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