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DAP

Data Analysis with PythonCertificate course in Data Analysis with Python - Data analysis is the process of extracting information from data. It involves multiple stages, including establishing a data set, preparing th…

Duration 3 Months Mode Online / Offline Eligibility graduation CITC Certified Placement Support

Data Analysis With Python (DAP)

Start Date 1 October 2026
Duration 3 Months
Mode Online / Offline
Certification CITC Certified
Batch / Course DAP
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Data Analysis With Python

Data Analysis with Python

CITC Courses Offer


Certificate course in Data Analysis with Python - 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. The goal of data analysis is to find actionable insights that can inform decision-making. Data analysis can involve data mining, descriptive and predictive analysis, statistical analysis, business analytics, and big data analytics.

Eligibility: 

To register for a certificate in Data Analytics with Python, students must earn a high school diploma. We provide multiple computer courses at an affordable price in Chandigarh, Mohali, and Kharar.  Learn from the best teachers, and get a valuable certificate, We have a great infrastructure, and a friendly environment, Join Us for a better future in the IT - sector.

Course:

Courses in Data Analysis with Python Online may include subjects such as Data Sets and Data Wrangling & Data Analysis, Importing Data Sets and Exploratory Data Analysis.

Online and offline computer courses are available in CITC  Register Now for a discount.

Course Papers / Subjects

What you will study in this programme

01
Data Sets, Data Wrangling and Data Analysis-Importing Data Sets
02
Model Development, Evaluation and Refinement-Model Development

Syllabus (Module-wise)

Expand each topic for details

Module 1

Course Modules/Papers

  • Data Sets and Data Wrangling and Data Analysis
  • Model Development, Evaluation and Refinement

  • Meaning of Data
  • How to use libraries in Python to import data from Multiple Sources
  • Analysis of Imported Data Set
  • Data Wrangling
  • Performing data wrangling tasks (like handling missing values in data, normalizing data, grouping data values into bins and converting categorical variables into numerical quantitative variables)
  • Meaning of Exploratory Data Analysis
  • Statistical Calculations such as Mean, Median, Mode and Quartile values
  • Using Pearson correlation method to compare two continuous numerical variables
  • Using the Chi-Square test to find the association between two categorical variables

  • Define Explanatory and Response variable
  • Interpretation and use of R-squared and Mean-square Errors measures to perform evaluations
  • Model Evaluation and Refinement
  • Importance of Model Evaluation
  • Understanding Data Model Refinement Techniques

What You Will Learn & Career Scope

Details from the course content


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