IBM
IBM Data Science Professional Certificate
IBM

IBM Data Science Professional Certificate

Prepare for a career as a data scientist. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from IBM. No prior experience required.

IBM Skills Network Team
Dr. Pooja
Abhishek Gagneja

Instructors: IBM Skills Network Team

Sponsored by InternMart, Inc

671,607 already enrolled

Earn a career credential that demonstrates your expertise
4.6

(76,757 reviews)

Beginner level
No prior experience required
Flexible schedule
4 months, 10 hours a week
Learn at your own pace
Build toward a degree
Earn a career credential that demonstrates your expertise
4.6

(76,757 reviews)

Beginner level
No prior experience required
Flexible schedule
4 months, 10 hours a week
Learn at your own pace
Build toward a degree

What you'll learn

  • Master the most up-to-date practical skills and knowledge that data scientists use in their daily roles

  • Learn the tools, languages, and libraries used by professional data scientists, including Python and SQL

  • Import and clean data sets, analyze and visualize data, and build machine learning models and pipelines

  • Apply your new skills to real-world projects and build a portfolio of data projects that showcase your proficiency to employers

Details to know

Shareable certificate

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Taught in English

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Advance your career with in-demand skills

  • Receive professional-level training from IBM
  • Demonstrate your technical proficiency
  • Earn an employer-recognized certificate from IBM
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$138,000+
median U.S. salary for Data Science
¹
69,000+
U.S. job openings in Data Science
¹
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Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

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Professional Certificate - 12 course series

What is Data Science?

Course 111 hours4.7 (73,646 ratings)

What you'll learn

  • Define data science and its importance in today’s data-driven world.

  • Describe the various paths that can lead to a career in data science.

  • Summarize  advice given by seasoned data science professionals to data scientists who are just starting out.

  • Explain why data science is considered the most in-demand job in the 21st century.

Skills you'll gain

Category: Data Analysis
Category: Data Processing
Category: Big Data
Category: Data Visualization
Category: Data Science
Category: Data Storytelling
Category: Analytics
Category: Business Analytics
Category: Business Intelligence
Category: Advanced Analytics
Category: Data Infrastructure
Category: Machine Learning
Category: Data Engineering
Category: Data Mining
Category: Extract, Transform, Load
Category: Data Architecture
Category: Data Storage
Category: Databases
Category: Data Management
Category: Computer Science

Tools for Data Science

Course 218 hours4.5 (29,332 ratings)

What you'll learn

  • Describe the Data Scientist’s tool kit which includes: Libraries & Packages, Data sets, Machine learning models, and Big Data tools 

  • Utilize languages commonly used by data scientists like Python, R, and SQL 

  • Demonstrate working knowledge of tools such as Jupyter notebooks and RStudio and utilize their various features  

  • Create and manage source code for data science using Git repositories and GitHub. 

Skills you'll gain

Category: Data Science
Category: Data Analysis
Category: Jupyter
Category: Software Versioning
Category: Git (Version Control System)
Category: Software Development Tools
Category: Software Configuration Management
Category: Application Programming Interface (API)
Category: GitHub
Category: Version Control
Category: Software Development
Category: Python Programming
Category: R Programming
Category: Statistical Programming
Category: CI/CD
Category: Development Environment
Category: Devops Tools
Category: IBM Cloud
Category: Integrated Development Environments
Category: Statistical Machine Learning

Data Science Methodology

Course 36 hours4.6 (20,513 ratings)

What you'll learn

  • Describe what a data science methodology is and why data scientists need a methodology.

  • Apply the six stages in the Cross-Industry Process for Data Mining (CRISP-DM) methodology to analyze a case study.

  • Evaluate which analytic model is appropriate among predictive, descriptive, and classification models used to analyze a case study.

  • Determine appropriate data sources for your data science analysis methodology.

Skills you'll gain

Category: Data Science
Category: Data Architecture
Category: Data Modeling
Category: Business Analysis
Category: Data Analysis
Category: Database Design
Category: Business Consulting
Category: Data Storytelling
Category: Data Visualization
Category: Business Analytics
Category: Data Quality
Category: Data Collection
Category: Analytics
Category: Data Management
Category: Data Governance

Python for Data Science, AI & Development

Course 425 hours4.6 (39,229 ratings)

What you'll learn

  • Learn Python - the most popular programming language and for Data Science and Software Development.

  • Apply Python programming logic Variables, Data Structures, Branching, Loops, Functions, Objects & Classes.

  • Demonstrate proficiency in using Python libraries such as Pandas & Numpy, and developing code using Jupyter Notebooks.

  • Access and web scrape data using APIs and Python libraries like Beautiful Soup.

Skills you'll gain

Category: Python Programming
Category: Computer Science
Category: Computer Programming
Category: Data Processing
Category: Pandas (Python Package)
Category: Data Manipulation
Category: Data Analysis
Category: Data Science
Category: NumPy
Category: Web Scraping
Category: Application Programming Interface (API)
Category: Object Oriented Programming (OOP)
Category: Jupyter
Category: Software Development
Category: Data Engineering
Category: Algorithms
Category: Data Structures
Category: Object Oriented Design
Category: Information Management
Category: Extract, Transform, Load

Python Project for Data Science

Course 58 hours4.5 (4,417 ratings)

What you'll learn

  • Play the role of a Data Scientist / Data Analyst working on a real project.

  • Demonstrate your Skills in Python - the language of choice for Data Science and Data Analysis.

  • Apply Python fundamentals, Python data structures, and working with data in Python.

  • Build a dashboard using Python and libraries like Pandas, Beautiful Soup and Plotly using Jupyter notebook.

Skills you'll gain

Category: Data Analysis
Category: Data Processing
Category: Python Programming
Category: Pandas (Python Package)
Category: Data Science
Category: Computer Science
Category: Jupyter
Category: Data Engineering
Category: Information Management
Category: Computer Programming
Category: Extract, Transform, Load
Category: Web Scraping

Databases and SQL for Data Science with Python

Course 620 hours4.7 (20,844 ratings)

What you'll learn

  • Analyze data within a database using SQL and Python.

  • Create a relational database and work with multiple tables using DDL commands.

  • Construct basic to intermediate level SQL queries using DML commands.

  • Compose more powerful queries with advanced SQL techniques like views, transactions, stored procedures, and joins.

Skills you'll gain

Category: SQL
Category: Database Development
Category: Database Management
Category: Relational Databases
Category: Database Systems
Category: Database Management Systems
Category: Query Languages
Category: Stored Procedure
Category: Database Design
Category: Data Modeling
Category: Database Architecture and Administration
Category: Data Management
Category: Data Access
Category: Database Administration
Category: Database Theory
Category: Databases
Category: Data Storage

Data Analysis with Python

Course 715 hours4.7 (18,651 ratings)

What you'll learn

  • Develop Python code for cleaning and preparing data for analysis - including handling missing values, formatting, normalizing, and binning data

  • Perform exploratory data analysis and apply analytical techniques to real-word datasets using libraries such as Pandas, Numpy and Scipy

  • Manipulate data using dataframes, summarize data, understand data distribution, perform correlation and create data pipelines

  • Build and evaluate regression models using machine learning scikit-learn library and use them for prediction and decision making

Skills you'll gain

Category: Data Science
Category: Data Analysis
Category: Pandas (Python Package)
Category: Correlation Analysis
Category: Statistical Modeling
Category: Statistical Analysis
Category: Statistics
Category: Predictive Modeling
Category: Predictive Analytics
Category: Scikit Learn (Machine Learning Library)
Category: Statistical Methods
Category: Analytics
Category: Regression Analysis
Category: Data Transformation
Category: Data Wrangling
Category: Supervised Learning
Category: Exploratory Data Analysis
Category: Data Manipulation
Category: Advanced Analytics
Category: Business Analytics

Data Visualization with Python

Course 820 hours4.5 (11,896 ratings)

What you'll learn

  • Implement data visualization techniques and plots using Python libraries, such as Matplotlib, Seaborn, and Folium to tell a stimulating story

  • Create different types of charts and plots such as line, area, histograms, bar, pie, box, scatter, and bubble

  • Create advanced visualizations such as waffle charts, word clouds, regression plots, maps with markers, & choropleth maps

  • Generate interactive dashboards containing scatter, line, bar, bubble, pie, and sunburst charts using the Dash framework and Plotly library

Skills you'll gain

Category: Data Visualization Software
Category: Data Visualization
Category: Data Presentation
Category: Exploratory Data Analysis
Category: Plot (Graphics)
Category: Statistical Visualization
Category: Interactive Data Visualization
Category: Plotly
Category: Data Analysis
Category: Matplotlib
Category: Datamaps
Category: Scatter Plots
Category: Business Intelligence
Category: Statistical Analysis
Category: Seaborn
Category: Data Science
Category: Descriptive Statistics
Category: Histogram
Category: Data Storytelling
Category: Dashboard

Machine Learning with Python

Course 913 hours4.7 (16,600 ratings)

What you'll learn

  • Describe the various types of Machine Learning algorithms and when to use them 

  • Compare and contrast linear classification methods including multiclass prediction, support vector machines, and logistic regression 

  • Write Python code that implements various classification techniques including K-Nearest neighbors (KNN), decision trees, and regression trees 

  • Evaluate the results from simple linear, non-linear, and multiple regression on a data set using evaluation metrics 

Skills you'll gain

Category: Applied Machine Learning
Category: Machine Learning
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Statistical Machine Learning
Category: Machine Learning Methods
Category: Supervised Learning
Category: Machine Learning Algorithms
Category: Regression Analysis
Category: Data Science
Category: Statistical Modeling
Category: Predictive Modeling
Category: Machine Learning Software
Category: Artificial Intelligence
Category: Predictive Analytics
Category: Analytics
Category: Data Analysis
Category: Unsupervised Learning
Category: Computer Science
Category: Classification And Regression Tree (CART)
Category: Scikit Learn (Machine Learning Library)

Applied Data Science Capstone

Course 1013 hours4.7 (7,199 ratings)

What you'll learn

  • Demonstrate proficiency in data science and machine learning techniques using a real-world data set and prepare a report for stakeholders 

  • Apply your skills to perform data collection, data wrangling, exploratory data analysis, data visualization model development, and model evaluation

  • Write Python code to create machine learning models including support vector machines, decision tree classifiers, and k-nearest neighbors

  • Evaluate the results of machine learning models for predictive analysis, compare their strengths and weaknesses and identify the optimal model 

Skills you'll gain

Category: Interactive Data Visualization
Category: Exploratory Data Analysis
Category: Statistical Analysis
Category: Data Presentation
Category: Data Visualization
Category: Applied Machine Learning
Category: Data Analysis
Category: Data Engineering
Category: Data Wrangling
Category: Statistics
Category: Business Analytics
Category: Predictive Analytics
Category: Data Science
Category: Dashboard
Category: Statistical Modeling
Category: Advanced Analytics
Category: Analytics
Category: Data Storytelling
Category: Predictive Modeling
Category: Plotly

Generative AI: Elevate Your Data Science Career

Course 1112 hours4.6 (130 ratings)

What you'll learn

  • Leverage generative AI tools, like GPT 3.5, ChatCSV, and tomat.ai, available to Data Scientists for querying and preparing data

  • Examine real-world scenarios where generative AI can enhance data science workflows

  • Practice generative AI skills in hand-on labs and projects by generating and augmenting datasets for specific use cases

  • Apply generative AI techniques in the development and refinement of machine learning models

Skills you'll gain

Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Artificial Intelligence
Category: Generative AI
Category: Data Science
Category: Data Strategy
Category: Statistical Analysis
Category: Exploratory Data Analysis
Category: Data Analysis
Category: Data Ethics
Category: Data Governance
Category: Computer Science
Category: Data Management

Data Scientist Career Guide and Interview Preparation

Course 129 hours4.8 (172 ratings)

What you'll learn

  • Describe the role of a data scientist and some career path options as well as the prospective opportunities in the field.

  • Explain how to build a foundation for a job search, including researching job listings, writing a resume, and making a portfolio of work.

  • Summarize what a candidate can expect during a typical job interview cycle, different types of interviews, and how to prepare for interviews.

  • Explain how to give an effective interview, including techniques for answering questions and how to make a professional personal presentation.

Skills you'll gain

Category: Professional Networking
Category: Interviewing Skills
Category: Interpersonal Communications
Category: Human Resources Management and Planning
Category: Communication
Category: Job Analysis
Category: Investment Management
Category: Financial Planning
Category: Recruitment
Category: Portfolio Management
Category: Business Research
Category: Market Research
Category: Human Resources
Category: Human Resource Management
Category: Communication Strategies
Category: Financial Management
Category: Market Intelligence
Category: Finance
Category: Market Analysis
Category: Wealth Management

Instructors

IBM Skills Network Team
IBM
58 Courses1,049,938 learners
Dr. Pooja
IBM
4 Courses314,875 learners
Abhishek Gagneja
IBM
5 Courses160,363 learners

Offered by

IBM

Build toward a degree

When you complete this Professional Certificate, you may be able to have your learning recognized for credit if you are admitted and enroll in one of the following online degree programs.¹

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Degree credit eligible

This Professional Certificate has ACE® recommendation. It is eligible for college credit at participating U.S. colleges and universities. Note: The decision to accept specific credit recommendations is up to each institution.

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¹Lightcast™ Job Postings Report, United States, 7/1/22-6/30/23. ²Based on program graduate survey responses, United States 2021.