Learn how to apply Python to data science, machine learning, data visualization, and automation. In this program, you will learn the necessary programming skills to manipulate databases and perform various levels of analysis on the data. You'll finish the program prepared to apply for entry-level data science and Python engineering positions.
You'll begin by learning Python programming fundamentals and using Numpy, Pandas, and Matplotlib to analyze data. After learning Python and its three main data science libraries, you will create predictive models from the data using machine learning packages such as Sci-Kit Learn. You will also use Python to automate everyday tasks such as aggregating, updating, and formatting data.
In the final unit, you will use Matplotlib, Seaborn, Plotly, and Dash Enterprise to create data visualizations and interactive dashboards that you can deploy to GitHub, where they will be easily accessible for potential employers to review.
From our hands-on training style to world-class instructors and custom-crafted curriculum, we deliver results our alumni are proud of.
Learn the concepts and skills covered in this program or your tuition is on us. See details and terms & conditions.
Work on projects proven to boost retention
Refined over many cohorts for an optimal learning experience
The teaching method at Noble Desktop is perfect and the classes provide you with infinite knowledge that makes you eager to take everything they offer. I love Noble!
—Ivonne Ackerman
Experienced educators who are driven to help you succeed
Refresh the materials for free within one year
Attend this certificate program in-person in NYC or Live Online via Zoom. Engage with expert instructors, ask questions, and get feedback on your exercises and projects.
Unlike other providers, these are not mass open-enrollment classes. At Noble Desktop, you’ll learn in small groups (typically 8-15 students) and receive personalized attention.
Get face-to-face interaction with an instructor and other students when you learn at our NYC campus. Courses are hands-on with a computer and software provided.
Get the same interactivity and access to the instructor as in-person students. There are no extra fees and we’ll work with you to ensure your remote setup is perfect.
Our instructors are veterans of their field and experienced educators, driven to help you succeed.
We want you to succeed in your career goals. In addition to 96 hours of hands-on, interactive training, you’ll also receive four 1-on-1 mentoring sessions where you can:
Upon completion of this course, you’ll receive an official certificate testifying to your mastery of the curriculum. We’ll send you a link where you can download your certificate, share it online with your friends, post it to your professional network on LinkedIn, and view all your earned certificates. Congratulations on your achievement!
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We offer a single free retake of any module or the whole program within a year.
You can also access recordings of each session in your student portal within one business day of the session’s end. Recordings are available for one month after the session.
This is the recommended order, but some courses may be taken in a different order.
Unit 1 30 Hours
Unit 2 30 Hours
Unit 3 6 Hours
Unit 4 24 Hours
Learn practical skills by working on real projects with instructor guidance and lectures to strengthen and improve your skill.
The Python Data Science & Machine Learning Bootcamp is best suited for:
In addition to 96 hours of interactive training, you will receive four 1-on-1 mentoring sessions that can be used for career and job support, including polishing your resume, preparing for interviews, and reviewing best practices for applying to jobs. Note, however, that we don’t provide job placement (i.e. reaching out to companies on your behalf).
Students must be comfortable using a computer. No other prior knowledge is required.
Yes, this course is eligible for our installment plan.
Learn more in the Financing section above.
You may attend this training virtually (online) at the scheduled time the course is offered (New York, Eastern Time).
You have some options:
