Data Analytics

 

Mastering Data Analytics: From Basics to Advanced Techniques

Who this course is for

What you'll learn

  • Master essential data skills including Python programming, NumPy, pandas, data collection, cleaning, preprocessing, visualization, analysis, and analytics.
  • Gain a thorough understanding of the data analyst role.
  • Learn Python from basic to advanced levels and Learn to efficiently work with text files.
  • Acquire both fundamental and advanced knowledge of NumPy and pandas.
  • Understand various data types and their memory implications.
  • Deepen your understanding of NumPy with statistics and preprocessing applications.
  • Master the art of data visualization, learning to create pie, bar, line, area, histogram, scatter, regression, and combo charts.
  • Engage in coding exercises designed to prepare you for a data analyst role.
  • Work with real-world data to solidify your skills.
  • Solve a final project that brings together all your newly acquired knowledge.

Learning Journey

The Course Includes

  • Classroom Training
  • 100+ Exercises
  • Study Materials
  • Certification
  • 1 to 1 Mentorship
  • Life-Time Community Membership
  • Hands-On Project
  • Interactive Webinars
  • Career Support

Course Highlight

Exceptional Faculty

Our instructors at Visual Labs are dedicated to teaching and possess over 12 years of professional experience.

Detailed Curriculum

Our courses are designed with industry relevance in mind, practical exposure with theoretical knowledge.

Practical Training

Students will engage in real-world data analytics projects across various domains to gain practical experience.

Career Preparation

From the very start, we provide rigorous interview preparation, connecting candidates with our extensive network.

Course Content

Introduction to the Course

Introduction to Data Analytics

Setting up the Environment

Python Basics

Fundamentals for Coding in Python

Mathematics for Python

NumPy Basics

Pandas- Basics

Working with Text Files

Working with Text Data

Must-Known Python Tools

Data Gathering/Data Collection

APIs

Data Cleaning and Data Preprocessing

pandas Series

pandas DataFrames

NumPy Fundamentals

NumPy DataTypes

Working with Arrays

Generating Data with NumPy- Preprocessing

A Loan Data example with NumPy

The "Absenteeism" excercise- Introduction

Data Visualization

Description

Our Data Analytics course is designed to provide you with the skills and knowledge necessary to thrive in the rapidly growing field of data analytics. Whether you’re an absolute beginner or a seasoned professional, this course covers everything from foundational concepts to advanced techniques, ensuring a comprehensive learning experience. Throughout the course, you’ll engage in hands-on projects, applying your knowledge to real-world scenarios through practical projects and case studies. Our expert instructors, with extensive experience in data analytics, will guide you through interactive sessions, group discussions, and collaborative activities to reinforce your learning. 

Projects

This project analyzes patient data to improve healthcare outcomes and hospital operations by identifying patterns and trends through statistical methods. Predictive modeling and visualizations are used to forecast patient outcomes.

This project analyzes employee data to identify factors influencing retention and turnover. Insights from job satisfaction, work environment, and compensation help predict departures and develop strategies.

This project analyzes customer loan data to enhance decision-making and risk management by identifying patterns and predicting default risks. Insights from demographics, loan amounts, and credit scores improve approval strategies.

This project analyzes data from an online store to identify sales trends and customer behaviors. Insights help optimize inventory, improve marketing strategies, and enhance customer satisfaction.

Skills Covered

Requirements

  • You’ll need to install Anaconda. We will show you how to do that step by step
  • Familiarity with Excel will be beneficial, but not mandatory.

Tools Required