Education

Data Scientist Course Eligibility Criteria: Syllabus, Skills, and Subjects

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Data science is a multidisciplinary field open to all professionals, whether engineers or marketers. Businesses depend on big data for decision-making, and data science has grown in popularity and demand.

In this article, you will learn about data scientists, their roles and skills, data scientist course eligibility criteria, and the syllabus – how to become one.

Data Scientist

What is data science?

Data science is an interdisciplinary field that collects and analyses large amounts of data to derive meaningful insights. It incorporates scientific techniques and theories from various fields, including mathematics, statistics, computer science, information science, and artificial intelligence.

Data science helps businesses in the following ways:

  • Make informed decisions
  • Measure performance and increase efficiency
  • Gauge market demand
  • Understand customer requirements and enhance their experiences.
  • Develop better products
  • Mitigate risk and fraud
  • Assess finances

Who are data scientists?

Data scientists provide expertise at various stages of the data science process. They analyze large amounts of data and provide actionable business growth and success insights.

Some of the roles and responsibilities of data scientists are:

  • Gather data and identify data sources
  • Analyse large amounts of structured or unstructured data to gain insights
  • Create business problem solutions and strategies
  • Predict trends and patterns, combine various algorithms and modules
  • Collaborate with teams and stakeholders to make data-driven decisions
  • Combine tools, applied statistics, and machine learning to create analytic solutions for businesses

What are the eligibility requirements for the data scientist course?

Anyone, whether a newcomer or a working professional, can pursue a career in data science. Engineers, marketing professionals, software developers, and IT professionals can enroll in online or part-time data science boot camps. However, basic high school-level subjects are required for regular courses.

Furthermore, a degree in one of the sciences, technology, engineering, or mathematics (STEM) fields gives you an advantage over others. It helps facilitate your understanding of data science concepts.

What is the data scientist course syllabus and subjects?

Below are some of the subjects of the data science course:

1. Mathematics

Data science involves lots of mathematical calculations. Machine learning and deep learning are also highly dependent on mathematics and statistics. In this subject, you will learn about the mathematical computations and formulae used in the data science process.

2. Programming

The data science curriculum emphasizes the study of various programming languages like Java, C, C++, Python, and others and their applications in business.

3. Probability and statistics

Effective data visualization, cleaning, and interpretation processes necessitate a thorough understanding of various probability and statistical approaches and techniques.

4. Data visualisation

Data visualization is an important aspect of the data science course. It helps data scientists convert insights into visual representations such as pie charts, graphs, and images. This makes them simple to understand for stakeholders and other professionals.

5. Machine learning

Machine learning (ML) is a branch of artificial intelligence (AI) that enables creative, intelligent robots to perform tasks that the human brain would perform. This subject will teach you about various types of ML systems and how to develop machine learning.

What are data scientist skills?

Data scientists require a specialized set of technical and non-technical skills. The following are some necessary skills needed for an aspiring data scientist.

1. Technical Skills

  • Statistical analysis and computing
  • Machine and deep learning
  • Programming and coding skills
  • Processing large data sets
  • Data visualization and wrangling
  • Statistics and mathematics

2. Non-technical skills

  • Strong business acumen
  • Strong communication skills
  • Critical thinking
  • Problem-solving skills
  • Collaboration

How do you become a data scientist?

In most cases, becoming a data scientist necessitates some formal education. Here are some steps to consider.

  • Get a degree in data science.
  • Improve your programming languages, machine learning, data visualization, big data, and communication skills.
  • Acquire an entry-level data analytics position.

Enrol in a data science degree online program. These online boot camps will teach you to use data science and analytics to gain revenue-generating insights and develop business growth strategies.

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