Become A Data Science Engineer In 60 Days


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About This Course

Deep Dive in Data Science Training. A Practical approach to learn Data Science. Become a Data  Science Expert
  • A Data Science Engineer is a professional who combines expertise in data science, engineering, and programming to extract valuable insights from data. This role involves a combination of skills from various disciplines, including statistics, machine learning, software development, and domain-specific knowledge.

Who this course is for

A data science course is typically designed for individuals who are interested in acquiring the skills and knowledge necessary to work in the field of data science. The target audience for such courses can be diverse, and it may include:

  • Aspiring Data Scientists
  • IT Professionals
  • Analysts and Statisticians
  • Business and Marketing Professionals
  • Graduate Students and Researchers
  • Entrepreneurs
  • Anyone Seeking Career Advancement
  • Programming Enthusiasts
  • Mathematics and Science Graduates
  • Career Changers

Course Content Download Here!


  • if you are a beginner then follow the course in same order and practice everything you learn.
  • you can always ask question in Q&A section. you will find it below every lecture. Please don’t use messages for asking doubts.
  • Your questions will be answered within 48 hours. before asking a question please check the question and answer for previously asked question.

What you’ll learn

In a data science course or program, participants typically acquire a wide range of skills and knowledge that enable them to effectively work with data, analyze it, and derive valuable insights. Here’s a general overview of what individuals can expect to learn from a data science curriculum:

  • Data Exploration and Preprocessing
  • Statistics and Mathematics for Data Science
  • Programming Skills
  • Data Visualization
  • Machine Learning Algorithms
  • Model Evaluation and Validation
  • Big Data Technologies
  • Database Management
  • Feature Engineering
  • Deep Learning (Optional)
  • Real-world Applications
  • Collaboration and Communication
  • Ethics and Privacy
  • Project Work
  • Continuous Learning

Are there any course requirements or prerequisites?

  • Mathematics, like probability, statistics, algebra, and calculus.
  • Object-oriented programming languages like Java, C, or Python.
  • Structured Query Language (SQL) for database queries.


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