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Data Analytics,Storage,Mining & Visual Big Data Technologies

Data Analytics,Storage,Mining & Visual Big Data Technologies

₹499

₹1399

Data Analytics, Data Storage, Data Mining and Data Visualization Big Data Technologies

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Has discount
Expiry period Lifetime
Made in English
Last updated at Mon Dec 2024
Level
Beginner
Total lectures 7
Total quizzes 1
Total duration 00:34:21 Hours
Total enrolment 0
Number of reviews 0
Avg rating
Short description Data Analytics, Data Storage, Data Mining and Data Visualization Big Data Technologies
Outcomes
  • Various Big Data Technology Fields
  • Big Data Technologies in Data Storage
  • Big Data Technologies in Data Visualization
  • Big Data Technologies in Data Mining
Requirements
  • 1. Educational Background High School Diploma or Equivalent: Most courses require at least a high school diploma or equivalent. Bachelor's Degree (Preferred but not always required): Some institutions may prefer candidates who have a bachelor's degree in a related field such as Computer Science, Engineering, Information Technology, or Mathematics, but this is not always a strict requirement.
  • 2. Prerequisite Knowledge and Skills While prior experience is not always mandatory, it can help if you are familiar with some basic concepts in data science, analytics, and programming: Basic programming knowledge: Familiarity with programming languages like Python or R is typically recommended. These languages are widely used in data analytics, mining, and visualization. Basic understanding of databases: Some knowledge of databases (e.g., SQL or NoSQL) will be useful, as the course covers topics like data storage and data retrieval. Basic statistics or math: Understanding fundamental concepts in statistics and mathematics is important for data analysis and mining. Some courses may recommend familiarity with concepts such as mean, median, regression, probability, and statistical tests.
  • 3. Software and Tools Access to a computer and internet: Since the course may be delivered online, you will need a computer with internet access. Software tools: Many of the tools covered in the course, such as Python, Apache Spark, and Hadoop, are open-source and free to use. For data visualization, tools like Tableau or Power BI may offer free versions for students or learners. Cloud computing access (optional): Some courses may provide access to cloud environments (e.g., AWS, Google Cloud Platform, Azure) for processing large datasets. Make sure you have the technical ability to access or set up cloud environments if required.
  • 4. Language Proficiency English proficiency: If the course is delivered in English, a basic understanding of English is necessary, especially for reading materials, understanding lectures, and completing assignments. Some institutions might require proof of English proficiency for non-native speakers, such as through TOEFL or IELTS scores.

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