Coursera IBM Data Science Professional Certificate Review will assist you if you want to pursue a career in Data Science. This certification consists of 9 courses that help you to acquire skills that are required to work on projects in the industry.
The lectures cover topics including data visualization, analysis, libraries, and open-source tools.
By the end of the program, you will have to finish multiple assignments and projects to showcase your skills and enhance your potential.
Data Science is rapidly permeating all industries and having a profound impact on virtually every aspect of our existence.
Data Science is becoming increasingly valuable, regardless of your field of business, expertise, or profession.
Coursera IBM Data Science Professional Certificate Review
To develop your skill in the data science area IBM has developed the Data Science Professional Certificate on Coursera.
It consists of 9 courses that are intended to arm you with the latest job-ready skills and techniques in Data Science.
The courses cover a variety of data science topics including open source tools and libraries, methodologies, Python, databases and SQL, data visualization, data analysis, and machine learning.
You will practice hands-on in the IBM Cloud (at no additional cost) using real data science tools and real-world data sets.
After completing the course you will become job-ready for a career in Data Science. You can develop practical skills using hands-on labs in Cloud environments, projects, and capstones.
Offered By: IBM
Rating: 4.6 out of 5.0
Students Enrolled: 233K+
Coursera IBM Data Science Professional Certificate taught by 5 Instructors.
- Joseph Santarcangelo, Ph.D., Data Scientist at IBM, IBM Developer Skills Network
- Alex Aklson, Ph.D., Data Scientist, IBM Developer Skills Network
- Rav Ahuja, AI, and Data Science Program Director, IBM
- SAEED AGHABOZORGI, Ph.D., Sr. Data Scientist, IBM Developer Skills Network
- Polong Lin, Data Scientist, IBM Developer Skills Network
Coursera IBM Data Science Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning.
No prior computer science or programming knowledge is necessary.
After completing this specialization, you can start with small, re-enforce applied learning, and build up to more complex topics.
You can Scale-up Your Skills in
- Data Science
- Machine Learning
- Python Programming
- Data Analysis
- Data Visualization (DataViz)
Coursera IBM Data Science Professional Certificate Specialization Review
The Coursera IBM Data Science certification program is designed to be highly personalized.
You can put your personality and interests into the projects you do and the types of analysis you complete.
No matter what field you are in or are hoping to join, data analytics is always present so be sure to mold the program to whatever type of work you are interested in.
Coursera Data Science Professional Certificate Includes-
There are 9 Courses in this Professional Certificate
Course 1: What is Data Science? (Rating: 4.7/5)
In the first online IBM data science professional certificate course, you will introduce to some data science practitioners and will get an overview of the basics of data science.
It went over the basic applications of data science, like data mining, linear regressions, real-world uses, etc.
In this tutorial, you will get some ideas from professionals or students, relaying their experiences in the field.
Course 2: Tools for Data Science (Rating: 4.6/5)
This short course goes through the most popular tools used in data science. It focused mostly on tools like Jupyter Notebooks, Zepplin, RStudio, and IBM Watson.
You will learn about what each tool is used for, what programming languages they can execute, and their features, and limitations.
From this tutorial, you will be able to test each tool and follow instructions to run simple code in Python, R, or Scala. To end the course.
After completing the section, you will be able to create a final project with a Jupyter Notebook on IBM Data Science Experience that you can share with your peers.
Course 3: Data Science Methodology (Rating: 4.6/5)
In this online tutorial, you will learn, the major steps involved in tackling a data science problem.
The major steps involved in practicing data science, from forming a concrete business or research problem to collecting and analyzing data, building a model, and understanding the feedback after model deployment.
You can learn how data scientists think.
Highly appreciated this course as here you can learn to think like a programmer and nowadays data science is one of the most challenging aspects of becoming a strong analyst.
Course 4: Python for Data Science and AI (Rating: 4.6/5)
You will be going to learn the basics of Python, Pandas, and NumPy in this tutorial. If you know the basics of python this course will be easy for you to complete.
In this Coursera IBM data science professional certificate course, students are required to analyze a set of economic data using Watson Studio.
The tutorial includes,
Python Basics, Types, Expressions and Variables, String Operations, Python Data Structures Lists, and Tuples Sets, Dictionaries, Python Programming Fundamentals, Conditions, and Branching Loops, Functions, Objects, and Classes, etc.
Finally, you will create your project to test your skills.
Course 5: Databases and SQL for Data Science (Rating: 4.7/5)
This course uses IBM Cloud as the main teaching platform. The course is well designed. You will learn how to collect and analyze data using Python.
The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL language.
The emphasis in this course is on hands-on and practical learning.
The Coursera IBM data science professional certificate will teach you to create a database instance in the cloud. You will also learn how to access databases from Jupyter notebooks using SQL and Python.
No prior knowledge of databases, SQL, Python, or programming is required.
Course 6: Data Analysis with Python (Rating: 4.7/5)
This course covers a range of data analysis techniques, from finding and wrangling data to statistical analysis and modeling.
This course will take you from the basics of Python to exploring many different types of data.
You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more.
This course also covers the following topics:
1) Importing Datasets 2) Cleaning the Data 3) Data frame manipulation 4) Summarizing the Data 5) Building machine learning Regression models
6) Building data pipeline Data Analysis with Python will be delivered through lectures, labs, and assignments.
Course 7: Data Visualization with Python (Rating: 4.6/5)
This online tutorial includes a rapid-fire introduction to a range of data visualization techniques, including line graphs, bar charts, pie charts, and specialized visualizations like Waffle and Folium.
The main goal of the Data Visualization with Python course is to teach you how to take data that at first glance has little meaning and present that data in a form that makes sense to people.
Various techniques have been developed for presenting data visually but in this course.
Course 8: Machine Learning with Python (Rating: 4.7/5)
This online course covers a lot of topics, including simple regression models, classification, clustering, and recommendation systems.
This course dives into the basics of machine learning using an approachable, and well-known programming language, Python.
In this course, we will be reviewing two main components: First, you will be learning about the purpose of Machine Learning and where it applies to the real world.
Second, you will get a general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms.
In this course, you can practice with real-life examples of Machine learning and see how it affects society
The final project for this course involves applying four different types of machine learning protocols to a data set to determine which is the best.
Course 9: Applied Data Science Capstone (Rating: 4.7/5)
Last the capstone project!
The capstone project for this program consisted of two parts. The final project of the capstone was entirely open-ended.
You can make up your question to answer using the tools you had learned. The only requirements were to use the Foursquare API, use data analytics, and build a Folium map as part of the presentation.
You will learn about location data and different location data providers, such as Foursquare.
This online course will teach you how to be creative in situations where data are not readily available by scraping web data and parsing HTML code.
You will utilize your knowledge of Python and its pandas library to manipulate data, which will help you refine your skills for exploring and analyzing data.
This capstone project course will give you a taste of what data scientists go through in real life when working with data.
IBM Data Science Career Opportunities
Coursera learner who completes this Professional Certificate will have special access to join IBM’s Talent Network.
Talent Network members receive all of the tools needed to land a dream job with IBM – sent directly to member’s inboxes.
You will get job opportunities as soon as they are posted, recommendations to apply matched directly to your skills and interests, and tips and tricks to help you stand apart from the crowd.
Some leading Data Science Careers are:
- Data Scientist
- Machine Learning Engineer
- Machine Learning Scientist
- Applications Architect
- Enterprise Architect
- Data Architect
- Infrastructure Architect
- Data Engineer
- Business Intelligence (BI) Developer
- Data Analyst
Earn a Coursera Credential
When you finish the course and complete the hands-on project, you’ll earn a Professional Certificate from IBM.
You can share the credential with prospective employers and your professional network.
Whether you’re looking to start a new career or change your current one to develop your career as a Data Scientist, Coursera IBM Data Science Professional Certificate Review helps you to become job-ready to start your career in Data Science.
This Career Credential will help you to unlock access to work in top universities and organizations easily.
If you subscribed, you will get a 7-day free trial during which you can cancel at no penalty. After that, you will not get any refunds, but you can cancel your subscription at any time.
This course uses a subscription-based payment model. There is a monthly fee of $39 that gives you access to all the course modules, assignments, discussion forums, and peer-graded assignments.
No matter how long it takes you to complete the courses, you will be charged the monthly fee unless you finish the program or cancel your subscription.
The duration of the Specialization is 10 months to complete, (approximately) 4 hours/ week.
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