Machines and robots from our childhood movies might not have taken over the world evidently, however, Artificial intelligence has made its way into every individual’s life who gets exposed to technology today. From personal assistants to driverless cars, from predictive techniques to personalization of digital ads, AI has seeped into our lives like never before. Thanks to improvement in power of computers, cheaper storage and enormous volumes of data being generated each day. Data science is used in industries for optimized products and services and for providing customers with personalized and highly targeted experiences. According to a statement by IBM, in the current year, job market will witness a tremendous rise in openings for data professionals. The demand is expected to rise from 364, 000 to 2,720, 000 (source). Commonly, the terms, “Artificial intelligence” and “Data science” are used interchangeably. Let’s have a clearer image of the relationship between the mind boggling but exciting concepts.

1. What is Data Science?

Data science is an area that uses scientific methods, algorithms, processes, and systems on structured and unstructured data to extract valuable insight and knowledge. It incorporates multiple underlying fields such as programming, mathematics and statistics. Knowledge of the disciplines is applied by data scientists to comprehend patterns in data. They should also be proficient in machine learning algorithms.

Data science experts assist in product development by providing the specifications based on the  behavior of customers. They conclude results that help in decision making and measuring performance.

2. What is Artificial Intelligence?

Artificial intelligence is cognitive capabilities demonstrated by machines such as  “problem solving” and “learning” that are associated with the human mind. It involves implementation of Machine learning algorithms to enable performing autonomous acts based on past actions. AI algorithms implemented today, such as deep learning algorithm does not need explicit definition of goals. It finds the goals autonomously by analyzing the patterns and trends in data.

Artificial intelligence experts assist in the fields of manufacturing, automation, robotics, transport, and healthcare. A survey conducted by Harvard Business Review concluded that 75 % of the executives in modern firms are certain about the idea that AI will have a significant impact on their firms within a time frame of three years. This study was conducted on 250 executives who were well aware of the use of cognitive technologies by their firms (source).

Lately, AI has done wonders in the field of e-learning. AI enabled Enterprise Learning Management Systems are providing personalized training solutions to workforce. Details will be explored later in the article.

But often people mix Data science and artificial intelligence with each other. Here are five key differences between Data Science and Artificial intelligence to clarify ambiguity.

3. Data science vs.  Artificial intelligence

-Data science involves statistical techniques while AI involves algorithmic techniques.

-Data science looks for hidden patterns for decision making whereas AI relies on intelligent reports for making decisions.

-Medium level processing of data is involved for data manipulation, on the other hand manipulation of data involves high order processing of data.

-Data science is represented by statistical graphical models while models that employ network nodes for imitating human cognitive processes are involved in AI.

-Data Science employs tools such as Python, SAS, R, SPSS and Keras while Artificial intelligence uses tools like Kafe, PyTorch, Shogun, TensorFlow and Mahout. 

4. Data science is a field that uses AI as a tool

Data science is a field that involves a comprehensive process involving multiple steps like data mining, data cleaning, data visualization, data exploration, and predictive modeling. Data scientists might use AI as a tool according to the business requirements. Machine learning algorithms are used in conjunction with statistical techniques for benefiting businesses.

Apart from other information intensive industries like health care, marketing and financial services, education and enterprise learning is an area where AI can make services cheaper and more valuable.

5. Artificial intelligence in e-learning

Technological advancements today are making it hard for workforce to synchronize with the pace and to be technology ready. Keeping up with the pace is highly critical in IT industry. The effectiveness of Enterprise Learning Management Systems plays an important role in increasing job performance for IT professionals. With the change in the digital landscape, interacting, learning, retaining and application of knowledge by modern learners has changed tremendously.

Organizations in the business of developing IT projects should have a learning platform that ensures career growth of employees keeping in view the business goals and the inherent needs of modern learners.

Needs of modern learners vary from person to person. according to IDC, 65% of learners have a preference of learning through formal learning sources as compared to the people who prefer informal sources.

AI enabled learning systems are a wonderful solution to meet the individual learning needs of the workforce and to increase the effectiveness of these systems. These systems prove to be an effective resource to improve the retention up to 60% (source).

Let's consider some benefits of AI in learning systems.

  • The adaptive nature of AI systems customizes learning experiences according to the competency levels. Predictive techniques are employed which expose highly engaging personalized content to the user.
  • Answering questions in real time becomes a reality.
  • AI works as a virtual assistant that can translate the content in the learner's native language, can read text and answers voice commands. Chatbots can be constant learning partner, even suggesting the learner what to study next.
  • Gading of assessments can be automated by AI.
  • It can identify the gaps in delivery of the concept and give feedback to learners instantly.

AI enabled learning systems have radically altered the learning experience. In future we might witness the role of trainer changed  to that of a facilitator and generation of the whole content by AI systems.

Quickstart offers an extremely intuitive Enterprise Learning Management System CLIPP. A unique propriety instructional delivery methodology has been created and it has been embedded in this cognitive learning platform. This system improves learner’s engagement by 30%, workforce readiness and goal attainment performance by 50%.

CLIPP comes with self-paced modular learning, Hands on labs, content from multiple sources aligned with the learner’s objectives and social interaction tools to enhance learning outcomes. Our instructors are leading experts from the IT industry.

If you are an IT service provider and want high impact learning experiences to your workforce to make it technology ready, CLIPP can prove to be the best resource for you.