IBM
IBM Data Science Professional Certificate
IBM

IBM Data Science Professional Certificate

Prepare for a career as a data scientist. Develop in-demand skills and hands-on experience to get job-ready in as little as 5 months. No prior experience required.

IBM Skills Network Team
Dr. Pooja
Abhishek Gagneja

Instructors: IBM Skills Network Team

Sponsored by Cisco Systems India Pvt Ltd.

7,610 already enrolled

Earn a career credential that demonstrates your expertise
4.6

(71,215 reviews)

Beginner level
No prior experience required
Flexible schedule
6 months, 10 hours a week
Learn at your own pace
Earn degree credit

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

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Taught in English
Recently updated!

June 2024

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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

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

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$138,000+
median U.S. salary for Data Science
¹
69,000+
U.S. job openings in Data Science
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Professional Certificate - 12 course series

What is Data Science?

Course 111 hours4.7 (69,383 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.

Tools for Data Science

Course 218 hours4.5 (28,494 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. 

Data Science Methodology

Course 36 hours4.6 (20,086 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.

Python for Data Science, AI & Development

Course 425 hours4.6 (36,095 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.

Python Project for Data Science

Course 58 hours4.5 (4,087 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.

Databases and SQL for Data Science with Python

Course 620 hours4.6 (19,692 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.

Data Analysis with Python

Course 715 hours4.7 (17,969 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

Data Visualization with Python

Course 820 hours4.5 (11,630 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

Machine Learning with Python

Course 913 hours4.7 (15,617 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 

Applied Data Science Capstone

Course 1013 hours4.7 (7,058 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 

Generative AI: Elevate Your Data Science Career

Course 1112 hours4.8 (35 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

Data Scientist Career Guide and Interview Preparation

Course 129 hours4.8 (66 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.

Instructors

IBM Skills Network Team
IBM
58 Courses814,243 learners
Dr. Pooja
IBM
4 Courses281,944 learners
Abhishek Gagneja
IBM
5 Courses116,602 learners

Offered by

IBM

Get a head start on your degree

When you complete this Professional Certificate, you can earn college credit if you are admitted and enroll in one of the following online degree programs.¹

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