Become a data science specialist. Acquire valuable competencies to further your journey in data science and enhance your career.

Earn your IBM Professional Certificate after successful completion of the program.

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Program details
  • IBM Professional Certificate

    Earn your professional certificate on completion

  • About this program

    09 Courses

    160 -220 Hours of content

    08 Skills

  • Includes

    86 Hands on labs - over 72 hours

    57 Quizzes

    189 Videos

  • Exercises to explore
    • Python
    • NumPy
    • Pandas
    • Matplotlib
    • GitHub
    • RStudio
    • IBM Cloud Db2
    • Jupyter notebook
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The IBM Data Science Professional Certificate provides learners with a thorough grounding in data science, the role of the data scientist in our world, and the approaches they use to solve real-world challenges. You will grow familiar with popular data science tools, including Jupyter notebooks, RStudio IDE, and IBM Cloud. And you will become skilled in using data science methodology to build, test, and train data models.

Additionally, you’ll learn how to work with Python, and become proficient in various Python libraries such as pandas and NumPy. And you will develop a project in Python to test and demonstrate your knowledge. Other skills you learn during the course will also enable you to design data science models and AI applications.

Through practice SQL exercises on real-world data sets, you’ll develop a thorough understanding of the role of SQL and databases. You’ll also create impactful visual representations of data with Python data visualization libraries – Matplotlib, Seaborn, and Folium. And you’ll be introduced to machine learning, including regression, classification, and clustering.

Your IBM capstone project will be to design and build a data model that endeavors to solve a real-world issue. This project will be submitted to IBM for evaluation.

This IBM Professional Certificate program comprises nine purposely designed courses that take you on a carefully defined tangible learning path. At the end of this learning path, you will submit a multi-faceted capstone project for evaluation by IBM.

It is a self-paced program, which means it is not run to a fixed schedule with regard to completing courses or submitting assignments. As long as the program is completed before the end date, you can work at your own pace. The materials for each course will become available when you start the particular course.

You can choose to enroll for the complete certification program in one go, or sign up for individual courses one at a time. Each course that you complete will take you a step closer to acquiring the IBM Professional Certificate. And it’s worth noting that some courses may also qualify for other learning paths.

Overall, for students keen to formalise their skills in data science, the IBM Data Science Professional Certificate is a superb opportunity to showcase your applied understanding of the subject. Please note that you must successfully complete the capstone project to complete the program and earn this IBM Professional Certificate.

  • Competence in building, testing, and training data models.
  • Practical knowledge of Python libraries; pandas and NumPy.
  • Thorough understanding of data science methodology.
  • Databases and SQL; practical application using real-world datasets.
  • Deep understanding of how machine learning works using Sci-Kit and SciPy.
  • In-depth knowledge of how data scientists solve real-world problems using data sets.
  • Valuable skills in Matplotlib, Seaborn, and Folium libraries to create impactful data visualizations.
  • Hands-on experience of implementing data science tools: Jupyter Notebook, RStudio IDE, and IBM Cloud.

Program Outline

This program is offered through a series of 9 courses.

Your IBM Professional Certificate will be issued once you have completed the full program and your capstone project has been successfully evaluated by IBM.

Enroll for this program

Discover the insights and trends in data.

Topics covered:

  • Why is data science such a sought-after field?

  • Key skills required to pursue a career in data science.

  • Insights from data science professionals.

  • Tools and algorithms used in data science practice.

  • What skills do you need to be a successful data scientist?

  • What is the role of data science within a business?

Course ID: AI0101EN-SkillUp

Learn how to use data science tools effectively.

Topics covered:

  • Popular data science tools; their features, and usage.

  • Mastering Jupyter Notebook, RStudio IDE, GitHub, and Watson Studio.

  • Testing tools on the IBM cloud platform using cognitive class labs.

  • Running simple code in Python and R.

  • Creating and sharing a Jupyter notebook.

Course ID: AI102EN-SkillUp

Acquire skills for tackling data science problems effectively.

Topics covered:

  • The major steps involved in tackling a data science problem.

  • The key stages in data science methodology; business understanding and analytic approach.

  • Solving data science problems; business understanding, analytic approach stages, data requirements, and data collection stages.

  • What is the purpose of data modeling? The characteristics of the modeling process.

  • What happens after model deployment?

  • The importance of model feedback.

Course ID: CB0103EN-SkillUp

Begin your data science programming journey with Python.

Topics covered:

  • Understanding Python; its fundamentals and uses.

  • Applying Python to data science.

  • Defining variables in Python.

  • Data structures and data analysis.

  • Performing I/O operations on files in Python.

  • How to use pandas; data analysis and manipulation in Python.

Course ID: IBM+PY0101EN-SkillUp+2020

Work with real databases, real data science tools, and real-world datasets.

Topics covered:

  • Applying foundational knowledge of the SQL language.

  • Creating a database in the cloud.

  • Using string patterns and ranges to query data.

  • Sorting and grouping data in result sets and by data type.

  • Analyzing data on a database using Python.

Course ID: CB0106EN-SkillUp

Acquire skills to predict future trends from data using Python.

Topics covered:

  • Analyzing data using Python.

  • Preparing data for analysis.

  • Creating meaningful data visualizations and predicting future trends from data.

  • Using pandas; learning to load, manipulate, analyze, and visualize datasets.

  • Understanding scikit-learn; how machine learning algorithms are used to build smart models and make predictions.

Course ID: CV0101EN-SkillUp

Create impactful data visuals using various Python libraries.

Topics covered:

  • Data visualization.

  • Data visualization libraries in Python; Matplotlib, Seaborn, and Folium.

  • Specialized visualization tools; pie charts, box plots, scatter plots, and bubble plots.

  • Advanced visualization tools; waffle charts, word clouds, Seaborn and regression plots.

  • Creating maps and visualizing geospatial data.

Course ID: CV0101EN-SkillUp

Gain a thorough understanding of machine learning and how it impacts society.

Topics covered:

  • Machine learning applications.

  • Overview of supervised and unsupervised learning.

  • Unsupervised learning algorithms; clustering and dimensionality reduction.

  • Relating statistical modeling to machine learning; how to compare them.

  • How machine learning affects society; real-life examples.

  • Recommender systems; two main types of engine.

Course ID: CV0101EN-SkillUp

Apply your new skills and knowledge to building a data model and checking its effectiveness.

Topics covered:

  • Data science and machine learning; a real-life scenario.

  • Analyzing and visualizing data using Python.

  • An engineering exercise using Python.

  • Building and validating a predictive machine learning model using Python.

  • Actionable insights into real-life data problems; create and share.

  • Capstone project for submission to IBM for evaluation.

Course ID: CV0101EN-SkillUp

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