Data Analysis with Python (DA0101EN) Data Analysis with Python (DA0101EN)

Data Analysis with Python

Data Analysis with Python (DA0101EN)

Course Provider

Data Analysis with Python

Course Highlights:

In this course, you will learn how to –

  • Analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using scikit-learn!
  • You will learn how to perform data analytics in Python using these popular Python libraries and you will do it using hands-on labs using real Python tools like Jupyter notebook in JupyterLab.
  • How to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data.
  • Co-branded certificate by FutureSkills Prime & SkillUp.

What will you learn in Data Analysis with Python course?

In this course you will learn about:

  • Data Acquisition
  • How to Obtain Basic Insight from a Dataset
  • Data Wrangling
  • Exploratory Data Analysis
  • Model Development
  • Model Evaluation

Data Analysis with Python

  • skill-type-icon Skill Type
    Emerging Tech
  • domain-icon Domain
    AI/BDA
  • course-category-icon Course Category
    Deepskilling Course
  • certified-earned-icon Certificate Earned Joint Co-Branded Participation Certificate
  • ssc-assesment-icon Nasscom assessment Available
  • course-covered-icon Course Covered under GoI Incentive
    Yes
    • cost-white-icon Course Price
      INR 2,999
      + 18% GST
    • duration-white-icon Course Duration
      9 Hours
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Why you should take Data Analysis with Python course?

This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more!

Who should take Data Analysis with Python course?

This course is designed for everyone who wants to learn how to analyze data using Python. You do not need programming experience for this. This course will take you from the very basics to exploring other advanced topics.

Curriculum

  • Module 1 - Introduction Learning Objectives Understanding the Domain Understanding the Dataset Python package for data science Importing and Exporting Data in Python Basic Insights from Datasets
  • Module 2 - Data Wrangling Identify and Handle Missing Values Data Formatting Data Normalization Sets Binning Indicator variables
  • Module 3 - Exploratory Data Analysis Descriptive Statistics Basic of Grouping ANOVA Correlation 2
  • Module 4 - Model Development Simple and Multiple Linear Regression Model Evaluation using Visualization Polynomial Regression and Pipelines R-squared and MSE for In-Sample Evaluation Prediction and Decision Making
  • Module 5 - Working with Data in Python Model Evaluation Over Fitting, Under fitting and Model Selection Ridge Regression Grid Search Model Refinement
  • Exam

Tools you will learn in Data Analysis with Python course

Jupyter Notebook

FAQs

Data is an essential part of any enterprise or business. It is critical to collect, process, and analyze data flow in a timely and accurate manner to discover information useful for decision making in business. The data science industry is rapidly expanding. Data volume can be large, making information handling difficult and time-consuming. Python is a popular programming language in scientific computing because it has many data-oriented feature packages that can speed up and simplify data processing, thus saving time. This article will focus on the distinct features of the Python programming language and what makes it a better choice for data analysis.

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