Training Level

Intermediate

Training Duration (Days)

85

Training Mode

Online

Prerequisite

  1. Basic Statistics and Mathematics
  2. A career as a data analyst requires a foundation in statistics and mathematics. Aspiring professionals of any educational background with an analytical frame of mind are best suited to pursue the Data Analyst Master’s Program.

Career Track

  1. BUSINESS ANALYST
  2. TECHNOLOGY ANALYST

Industry Skill
Framework

Accreditation Body

IBM

Skill Outcome

By the end of this course, you will be able to:

  1. Learn how to interpret data in Python using multi-dimensional arrays in NumPy, manipulate DataFrames in Pandas, use SciPy library of mathematical routines, and execute machine learning using Scikit-Learn   Perform data analytics using popular Python librariesGain Inight on several data visualization libraries in Python, including Matplotlib, Seaborn and folium
  2. Write your first Python program by implementing concepts of variables, strings, functions, loops, and conditions   Understand the nuances of lists, sets, dictionaries, conditions and branching, objects, and classes in Python  Gain an In depth understanding on the basics of R and get to write your own R scripts
  3. Master R Programming and understand how various statements are executed in R
  4. Understand essential statistical concepts, including measures of central tendency, dispersion, correlation, and regression
  5. Understand essential statistical concepts, including measures of central tendency, dispersion, correlation, and regression
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