Contact Info

  • Mon - Fri: 9:00 - 18:00

  • General Inquiries - 079 4004 1819
  • info@waytowebeducation.com
  • 402, Samedh Complex, C.G Road, Above Punjab National Bank, Near Associate Petrol Pump, Ahmedabad, Gujarat 380006

Data Science

Python & Data Science

About This Course

Data is the new oil, and Python is the tool used to extract its value. This Python & Data Science course by WayToWeb Pvt. Ltd. is designed to take you from a complete beginner to a proficient data professional.

You will learn to write clean Python scripts, manipulate massive datasets, create compelling visual dashboards, and implement foundational machine learning algorithms to solve real business problems.

Step-by-Step Curriculum

We teach this course through a structured, hands-on approach:

  • Step 1: Core Python Programming: Master syntax, data structures, loops, functions, and object-oriented programming in Python.

  • Step 2: Data Manipulation (Pandas & NumPy): Learn to clean, filter, and transform messy real-world datasets efficiently.

  • Step 3: Data Visualization: Create stunning charts and interactive dashboards using Matplotlib, Seaborn, and Plotly.

  • Step 4: Exploratory Data Analysis (EDA): Discover hidden patterns, trends, and actionable insights from raw data.

  • Step 5: Intro to Machine Learning: Build your first predictive models using Scikit-Learn (e.g., predicting sales, classifying customer types).

Material Includes

  • Real-world messy datasets for practice

  • Jupyter Notebook templates and cheat sheets

  • End-to-end Data Analysis Capstone Project

Requirements

  • No prior programming experience needed

  • Basic high-school level mathematics

  • An analytical mindset and curiosity to solve problems

Target Audience

  • Beginners starting their IT career

  • Business Analysts wanting to transition to Python

  • Automation enthusiasts and researchers

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Contact for Fee

  • Level

    Beginner to Intermediate

  • Duration

    3 - 5 Months

  • Subject

    Data Science

  • Language

    Hindi / English

  • Mode

    Online & Offline

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