Data Science For Beginners

Data cleaning, Data wrangling, Data transforming

What you'll learn

Understand the need of Data and Data Science

Identify the different data structures to represent data

Identify data manipulation and cleaning techniques using pandas

Visualize and understand the patterns in data

Requirements

You will learn everything need to know here

Description

This comprehensive course offers a structured introduction to the world of data science, combining foundational theory with practical skills in Python programming. Beginning with the basics, you'll explore what data is, understand the role and scope of data science, and delve into essential statistical concepts. You'll learn about key sampling techniques and descriptive statistics, which form the basis for insightful data interpretation.The course then moves into Python fundamentals tailored for data science, covering data types, control flow, functions, and object-oriented programming. With these skills, you'll be equipped to handle data efficiently and write clean, reusable code.Next, you’ll be introduced to two essential Python libraries—NumPy and Pandas—that are pivotal for numerical operations and data manipulation. You’ll practice creating and analyzing datasets using Pandas Series and DataFrames.In the final section, you'll develop hands-on experience with exploratory data analysis (EDA), learning techniques for data acquisition, wrangling, cleaning, and preparation. These are critical steps before applying advanced analytics or machine learning. Each section will have quiz to assess your performance.By the end of the course, you will have a strong understanding of how to use Python and data science principles to extract meaningful insights from raw data, setting a strong foundation for your journey in data science.

Overview

Section 1: Introduction of Data and Data Science

Lecture 1 Introduction to Data, Data science

Lecture 2 Sampling

Lecture 3 Descriptive Statistics

Section 2: NumPy & Pandas

Lecture 4 NumPy

Lecture 5 Pandas Series and DataFrames

Section 3: Data Science Process

Lecture 6 Data Cleaning and Preparation

Lecture 7 Data Wrangling

Lecture 8 Data Transformation

Beginners who wish to pursue their career in Data Science