Beginner-friendly Python Certification for Data Science

Table of Contents

1. Introduction to Python for Data Science
2. Python Basics
   • Types, Expressions, and Variables
   • STRING Operations
3. Python Data Structures
   • Lists
   • Tuples
   • Sets
   • Dictionaries
4. Python Programming Fundamentals
   • Conditions
   • Loops
   • Functions
   • Objects and Classes
5. Working with Data in Python
   • Reading Files with Open
   • Writing Files with Open
   • Working with Pandas
   • APIs
6. Introduction to the Cloud
7. Introduction to Data Science
8. Spark
9. Hadoop
10. SQL and Relational Databases
11. Bitcoin and Cryptocurrency
12. Python for Data Science Final Exam

Python for Data Science: An Introduction to the Basics

Python for Data Science is an entry-level certification course offered by Cognitive Class, an initiative by IBM. This course focuses on providing a solid foundation in the Python programming language for individuals interested in pursuing a career in data science.

Python Basics

The first module of the course covers the basics of Python programming. You will learn about types, expressions, and variables, as well as various string operations. Through interactive labs and quizzes, you will gain hands-on experience and develop your understanding of Python fundamentals.

Python Data Structures

In the Second module, you will dive into Python data structures such as lists, tuples, sets, and dictionaries. Understanding these data structures is essential for organizing and manipulating data effectively. The module includes labs and review questions to reinforce your learning.

Python Programming Fundamentals

Module three focuses on essential programming concepts in Python. You will learn about conditions, loops, functions, and object-oriented programming. This module lays the groundwork for writing efficient and reusable code. Labs and practice exercises are provided to sharpen your programming skills.

Working with Data in Python

The fourth module delves into working with data in Python. You will learn how to Read and write files, work with the popular data manipulation library Pandas, and Interact with APIs. These skills are crucial for data analysis and understanding the real-world applications of Python in data science.

Introduction to the Cloud and Data Science

Modules five and six introduce the cloud and the field of data science, respectively. You will understand how cloud technologies like IBM Cloud, Amazon Web Services, and Microsoft Azure support data storage and processing. Additionally, you will gain insights into the multidisciplinary field of data science and its applications across various industries.

Spark, Hadoop, SQL, and Cryptocurrency

The course also covers advanced topics such as Apache Spark, Hadoop, SQL, and the basics of cryptocurrency like Bitcoin. These topics expand your knowledge and equip you with additional tools for handling big data and exploring cutting-edge technologies.

Python for Data Science Final Exam

Upon completing all the modules, you will need to pass the final exam to earn the Python for Data Science certification. This exam assesses your understanding of the course material and your ability to Apply Python programming principles in practical scenarios.

By completing this course with flying colors, you will receive the Python for Data Science certification and an IBM-issued badge. You can showcase this achievement on your resume and share it on various social media platforms.

Note: The course also offers Jupyter notebooks for practicing and honing your Python programming skills. These notebooks provide an interactive environment for writing and executing Python scripts.

In conclusion, Python for Data Science is an excellent starting point for beginners who want to gain proficiency in Python programming and pursue a career in data science. The course provides comprehensive coverage of the essential concepts and tools required in the field. Start learning today and unlock the doors to a promising future in data science.

Pros

• Beginner-friendly course
• Well-structured modules and labs
• Offers in-depth coverage of Python programming
• Hands-on experience with real-world datasets
• Recognized certification from IBM

Cons

• Limited focus on advanced data science techniques
• No practical projects included

Highlights

• Beginner-friendly certification course on Python for Data Science.
• Covers Python basics, data structures, programming fundamentals, and working with data.
• Introduction to cloud technologies and data science.
• Advanced topics include Spark, Hadoop, SQL, and cryptocurrency.
• Final exam to earn the Python for Data Science certification.
• IBM-issued badge and the option to share the certification on social media.
• Interactive Jupyter notebooks for practice and learning.

FAQ

Q: Is this course suitable for beginners? A: Yes, Python for Data Science is designed for individuals with little to no programming experience. It provides a solid foundation in Python and data science concepts.

Q: Can I get a certification after completing this course? A: Yes, upon successfully passing the final exam, you will receive the Python for Data Science certification issued by IBM.

Q: Are there any prerequisites for this course? A: No, there are no prerequisites. This course is suitable for anyone interested in learning Python for data science.

Q: How long does it take to complete the course? A: The estimated effort to complete the entire course is approximately three hours. However, you can learn at your own pace as it is a self-paced course.

Q: Can I share my certification on social media? A: Yes, once you earn the certification, you can share it on platforms like Facebook, Twitter, and LinkedIn.

Q: Are there any practical projects included in the course? A: No, the course focuses on providing a foundational understanding of Python for data science. Practical projects are not included.

Q: Is the course recognized in the industry? A: Yes, the Python for Data Science certification issued by IBM carries recognition in the industry and can be a valuable addition to your resume.