Data Analysis With Python

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Batch Name
DAP

Course Start
1-April-2024

Course duration
90 Hours

Eligibility
graduation

Data Analysis with Python

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.

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Course Modules/Papers

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

Course Syllabus

Data Sets, Data Wrangling and Data Analysis Importing Data Sets

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

Model Development, Evaluation and Refinement Model Development

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

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CITC Courses Query

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