IDSB: Introduction to Data Science for Beginners

· Take the next step in your career! Whether you’re an aspiring professional, experienced executive, or budding Data Science enthusiast, this course is your gateway to sharpening your Data Science capabilities and making a significant impact in your career or organization.

· With this course as your guide, you learn how to: Understand core Data Science concepts, including data analysis, statistics, and machine learning, to solve real-world problems effectively.

· Enhance your ability to apply theoretical knowledge to practical challenges in data handling, visualization, and prediction.

· Gain proficiency in key tools and techniques like data mining, regression, and clustering for insightful analysis.

· Develop a solid foundation for career advancement, with practical case studies, frameworks, and interactive exercises to hone your expertise.

The Frameworks of the Course

• Engaging video lectures, case studies, assessments, downloadable resources, and interactive exercises. This course is created to introduce you to Data Science, covering key concepts such as data collection, preparation, and analysis. You will learn about the role and responsibilities of a Data Scientist, and the importance of Data Science in solving real-world problems. Key topics will include understanding data accuracy, reliability, and core statistical concepts to interpret data and make informed decisions. You will also explore data mining techniques to effectively communicate findings, and dive into the basics of machine learning for predictive modeling.

• Communication Skills: You will learn the importance of clear and effective communication in Data Science. Topics will cover verbal communication for presenting data insights, active listening techniques for collaborative problem-solving, and how to communicate findings effectively to non-technical stakeholders. You will also understand how to structure written reports, emails, and documentation in a professional way. Additionally, the course will cover non-verbal communication such as body language and how to build rapport with colleagues in Data Science teams. You will also explore office technology and tools relevant to Data Science, including software used for data visualization and analysis, as well as basic troubleshooting for Data Science-related tools.

The course includes multiple case studies, resources such as templates, worksheets, reading materials, quizzes, self-assessments, and hands-on assignments to nurture and enhance your understanding of Data Science concepts. You will also have access to real-world data analysis projects where you can apply theoretical knowledge to practical issues, learning how to work with real datasets and make data-driven decisions.

In the first part of the course, you’ll learn the fundamentals of Data Science, including an introduction to its key concepts such as data collection, data preparation, and the importance of data accuracy and reliability. You’ll explore the role and responsibilities of a Data Scientist and understand the critical skills required to work effectively in this field. This section will also cover core statistical concepts that form the foundation of data analysis and help in making informed decisions based on data.

In the middle part of the course, you’ll develop your understanding of data analysis tools and techniques. You’ll gain hands-on experience with data visualization to present insights clearly, and learn the basics of machine learning for building predictive models. This section will also explore how to communicate data insights effectively, covering skills such as verbal communication, active listening, and presenting data findings to non-technical audiences. The course will also dive into office technologies relevant to Data Science, including essential software tools and advanced features of data analysis platforms.

In the final part of the course, you’ll develop your skills in organizing and managing data workflows. You will learn how to prioritize data-related tasks, set data analysis goals, and use tools to track progress and manage projects effectively. You’ll also gain insights into how to plan and organize data-driven projects, including understanding how to structure data pipelines and coordinate team efforts. Additionally, you’ll receive continuous support with guaranteed responses to all your queries within 48 hours, ensuring that you can apply what you’ve learned to real-world data problems effectively.

Course Content:

Part 1

Introduction and Study Plan

Introduction, Study Plan and Structure of the Course

Module 1: About to Data Science

Lesson 1: Overview of Data Science

Lesson 2: Major Application of Data Science

Lesson 3: Brief about Interdisciplinary Field

Module 2: Statistics

Lesson 1: Sampling

Lesson 2: Descriptive Statistics

Lesson 3: Hypothesis Testing

Lesson 4: Regression

Lesson 5: Forecasting

Lesson 6: ANOVA

Module 3: Probability and Distribution

Lesson 1: Probability

Lesson 2: Mathematical Rules in Probability

Lesson 3: Probability Distribution

Part 2

Module 4: Data Mining

Lesson 1: About Data Mining

Lesson 2: Data Structure

Lesson 3: Major Application

Module 5: Machine Learning

Lesson 1: Machine Learning Techniques

Lesson 2: Other Methods

Module 6: Tools and Function

Lesson 1: Business Intelligent Tools

Assignment: Data Science