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Python for Data Science

Python for Data Science: From Basics to Data-Driven Insights

★ 4.2 (27 ratings)2 WeeksCertificate

About This Course

This program introduces the fundamentals of Python, emphasizing its applications in data science. Participants will learn to use Python for data manipulation, performing basic data analysis, creating visualizations, and understanding basic machine learning concepts.

Aim

To provide learners with foundational skills in Python programming, focusing on data analysis, visualization, and introductory machine learning concepts. This course aims to equip participants with essential tools to manipulate, analyze, and visualize data efficiently using Python.

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Program Objectives

  • Gain a strong foundation in Python programming.
  • Learn to manipulate and analyze data using Python libraries.
  • Create effective data visualizations.
  • Understand basic machine learning concepts.
  • Apply Python skills to real-world data science problems.

Program Structure

  • Module 1: Python Basics 
    1. Introduction to Python
      • Understanding Python’s role in data science
      • Setting up Python environment (Anaconda, Jupyter Notebook)
      • Basic syntax, variables, and data types
    2. Control Structures 
      • If-else statements
      • For and while loops
      • List comprehensions
    3. Functions and Modules 
      • Defining functions
      • Importing and using libraries (NumPy, Pandas, Matplotlib)
      • Writing and organizing Python scripts
    4. Basic Data Structures 
      • Lists, tuples, dictionaries, and sets
      • Manipulating and accessing data structures

    Module 2: Data Manipulation with Pandas 

    1. Introduction to Pandas 
      • Understanding DataFrames and Series
      • Loading data from CSV, Excel, and other file formats
    2. Data Cleaning and Preprocessing 
      • Handling missing data
      • Filtering, sorting, and grouping data
      • Applying functions across data
    3. Data Transformation 
      • Merging, joining, and concatenating DataFrames
      • Pivot tables and cross-tabulation
      • Data aggregation and summarization

    Module 3: Data Visualization with Matplotlib 

    1. Introduction to Data Visualization 
      • Importance of visualization in data science
      • Overview of Matplotlib and Seaborn
    2. Creating Basic Plots 
      • Line plots, bar charts, and histograms
      • Customizing plots: labels, titles, and legends
    3. Advanced Visualization Techniques 
      • Scatter plots, box plots, and heatmaps
      • Multiple plots and subplots
      • Saving and exporting visualizations

Who Should Enrol?

Beginners in programming, data analysts, researchers, and students in data science.

Program Outcomes

  • Proficiency in Python for data analysis and visualization.
  • Ability to manipulate and analyze datasets using Python.
  • Basic understanding of machine learning concepts.
  • Capability to create data visualizations and interpret them.
  • Hands-on experience with Python tools in data science.
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Fee Structure

Discounted: ₹5500 | $61

We accept 20+ global currencies. View list →

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Frequently asked questions

Will I get the recording?

Yes. Paid participants get the session recordings and study material in their NanoSchool dashboard (My registrations → Recorded Lectures / Study Material).

What if I miss a live session?

Watch the recording in your dashboard and send your questions to the mentor through the support desk.

Do I get a certificate?

Yes, an e-certificate of participation after the workshop, with a QR code anyone can verify and an "Add to LinkedIn" button.

Which fee category applies to me?

Choose the category that matches your current role: Student, Ph.D. Scholar / Researcher, Academician / Faculty or Industry Professional.

How can I pay?

By card, UPI or PayPal on the payment page; international bank transfer is also available there.

What is the refund policy?

See our Returns, Refunds & Cancellation policy: Returns, Refunds & Cancellation policy

Need Help?

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WhatsApp +91 99581 61117

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