Introduction to Data Science and Analytics

About Course

This course is designed to provide a comprehensive introduction to Data Science and Analytics, covering essential concepts, tools, and techniques. Students will learn how to analyze data, build predictive models, and derive insights that can drive decision-making in various industries.

Understand the core principles of Data Science, including its definition, significance, and the various methodologies used in the field.
Gain proficiency in data collection, cleaning, and exploratory data analysis (EDA) using programming languages like Python and SQL.
Learn to build, evaluate, and deploy machine learning models for predictive analytics and decision-making.
Explore how Data Science is applied across different industries, including healthcare, finance, and retail, to drive innovation and improve outcomes.

Course Content

MODULE 1: INTRODUCTION TO DATA SCIENCE
In this module, students will learn the fundamentals of Data Science, which combines statistics, mathematics, and computer science to extract insights from data.

Overview of Data Science
Data Science Lifecycle
TEST ON INTRODUCTION TO DATA SCIENCE

MODULE 2: PRACTICING THE BASICS
This module will give students foundational knowledge and hands-on experience in programming for data science using Python.

MODULE 3: STATISTICS AND PROBABILITY
This module on Statistics and Probability provides a comprehensive introduction to essential concepts and techniques.

MODULE 4: MATHEMATICAL FOUNDATIONS
The Mathematical Foundations module provides a solid understanding of linear algebra and calculus concepts that are essential for data science and machine learning.

MODULE 5: EXPLORATORY DATA ANALYSIS (EDA)
This module on Exploratory Data Analysis (EDA) emphasizes the importance of data cleaning and visualization in the data analysis process.

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Student Ratings & Reviews

5.0

Total 3 Ratings

3 Ratings

0 Rating

7 months ago

Informative, engaging, practical. The course delivers essential insights for those aiming to enhance their online marketing capabilities.

7 months ago

Engaging, practical, essential. The course equips learners to excel in online marketing strategies effectively and efficiently

7 months ago

Dynamic, practical, transformative. The course empowers learners to master effective online marketing strategies with confidence and clarity.

About Course

What Will You Learn?

Course Content

MODULE 1: INTRODUCTION TO DATA SCIENCE
In this module, students will learn the fundamentals of Data Science, which combines statistics, mathematics, and computer science to extract insights from data.

Overview of Data Science

Data Science Lifecycle

TEST ON INTRODUCTION TO DATA SCIENCE

MODULE 2: PRACTICING THE BASICS
This module will give students foundational knowledge and hands-on experience in programming for data science using Python.

Python for Data Science

Introduction to SQL

Introducing the SELECT Statement for Retrieving Data

TEST ON PYTHON AND INTRODUCTION TO SQL

MODULE 3: STATISTICS AND PROBABILITY
This module on Statistics and Probability provides a comprehensive introduction to essential concepts and techniques.

Introduction to Statistics

Data Collection and Sampling Techniques

Descriptive Statistics

Probability Basics

Conditional Probability

Discrete Probability Distributions

Continuous Probability Distributions

Hypothesis Testing

Correlation and Regression

TEST ON STATISTICS AND PROBABILITY

MODULE 4: MATHEMATICAL FOUNDATIONS
The Mathematical Foundations module provides a solid understanding of linear algebra and calculus concepts that are essential for data science and machine learning.

Linear Algebra

Calculus

TEST ON MATHEMATICAL FOUNDATIONS

MODULE 5: EXPLORATORY DATA ANALYSIS (EDA)
This module on Exploratory Data Analysis (EDA) emphasizes the importance of data cleaning and visualization in the data analysis process.

Data Cleaning

Data Visualization

QUIZ ON EXPLORATORY DATA ANALYSIS (EDA)

Earn a certificate

Introduction to Entrepreneurship

How to Create a Winning Business Plan That Attracts Investors

The Art of Negotiation: Practical Approaches for Every Situation

Introduction to Business Management

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Introduction to Data Science and Analytics

About Course

What Will You Learn?

Course Content

MODULE 1: INTRODUCTION TO DATA SCIENCE In this module, students will learn the fundamentals of Data Science, which combines statistics, mathematics, and computer science to extract insights from data.

TEST ON INTRODUCTION TO DATA SCIENCE

MODULE 2: PRACTICING THE BASICS This module will give students foundational knowledge and hands-on experience in programming for data science using Python.

TEST ON PYTHON AND INTRODUCTION TO SQL

MODULE 3: STATISTICS AND PROBABILITY This module on Statistics and Probability provides a comprehensive introduction to essential concepts and techniques.

Conditional Probability

TEST ON STATISTICS AND PROBABILITY

MODULE 4: MATHEMATICAL FOUNDATIONS The Mathematical Foundations module provides a solid understanding of linear algebra and calculus concepts that are essential for data science and machine learning.

TEST ON MATHEMATICAL FOUNDATIONS

MODULE 5: EXPLORATORY DATA ANALYSIS (EDA) This module on Exploratory Data Analysis (EDA) emphasizes the importance of data cleaning and visualization in the data analysis process.

QUIZ ON EXPLORATORY DATA ANALYSIS (EDA)

Earn a certificate

Student Ratings & Reviews

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MODULE 1: INTRODUCTION TO DATA SCIENCE
In this module, students will learn the fundamentals of Data Science, which combines statistics, mathematics, and computer science to extract insights from data.

MODULE 2: PRACTICING THE BASICS
This module will give students foundational knowledge and hands-on experience in programming for data science using Python.

MODULE 3: STATISTICS AND PROBABILITY
This module on Statistics and Probability provides a comprehensive introduction to essential concepts and techniques.

MODULE 4: MATHEMATICAL FOUNDATIONS
The Mathematical Foundations module provides a solid understanding of linear algebra and calculus concepts that are essential for data science and machine learning.

MODULE 5: EXPLORATORY DATA ANALYSIS (EDA)
This module on Exploratory Data Analysis (EDA) emphasizes the importance of data cleaning and visualization in the data analysis process.