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Data Analysis and Visualization (Stand-Alone Course)

Data analysis and visualization program is created for beginners who have never programmed before and want to build a complete understanding of Python from the ground up as well as begin the artificial intelligent, machine learning or data science track.

  • Data analysis is the process of extracting information from data. It involves multiple stages, including establishing a data set, preparing the data for processing, applying models, identifying key findings and creating reports. Data analysis aims to find actionable insights that can inform decision-making. This course teaches you essential statistical knowledge and how to apply it to different business questions. After completing this course, you can analyze your data quickly and visualize your results using SPSS and Python. You don’t need any prior knowledge to enroll in this course. You will learn how to use Python to analyze and visualize your data using different libraries. You will explore the four crucial steps for any data analysis project: Reading, describing, cleaning and visualizing data. In each step, you will work with the most common and popular tools data analysts use daily. By the end of the course, you will be able to extract knowledge and answers from data confidently.

    Code

    Title

    CEUs*
    CDAV101

    Data analysis & Visualization

    3

    *Continuing education unit equals 10 contact hours.

    A stand-alone certificate will be issued upon the successful completion of each course.

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

    1. Utilize statistical tools for working with data sets
    2. Practice SPSS data entry, editing and organizing datasets, and carrying out inferential statistical analysis
    3. Use Python to solve tasks
    4. Practice using NumPy for data analysis
    5. Manage pandas in a data analysis context
    6. Manage data import and cleaning for different types of data
    7. Practice using different data visualization libraries and extracting insights from them
    8. Analyze machine learning algorithms for working with datasets
    • Applicants must pass the Standardized English Proficiency Test (SEPT/OEPT) and score level ENGG B1A
    • Previous awareness of Excel sheets
  • Tuition Type Fees (EGP) Important Notes
    Course Tuition/3 CEUs 2,500 Refund Policy
    Admission Fees 100 One-time admission non-refundable fee
    Standardized English Proficiency Test (SEPT) - Face to Face Test 400 Until 6 working days before the beginning of the term.
    Online English Placement Test (OEPT) - Online Test 340 Until 4 working days before the beginning of the term.
    One-day service Test 550 Until 5 working days before the beginning of the term.
    • Learners should choose Face to Face (SEPT) test OR Online test (OEPT)
    • Exam fees are non-refundable and changes in admission test dates are only allowed two working days in advance of the reserved test session according to the availability by sending an email to sce@aucegypt.edu. 

New Students - Apply Now    Continuing Students - Register Here

Course Info

Duration:
30 hours
Subject:
Database Management
Location:
AUC Tahrir Square
AUC New Cairo
Off Campus
Format:
In class/Online
CEUs:
3
Status
Available

Dates: To know more about the registration deadline and term dates, click here.

Contact Us

Email: sce@aucegypt.edu

Hotline: 16723

More Info