Data Science and Machine Learning with Python - Hands On!
Skillshare · Skillshare Instructor · Updated
AI Tutor Rating
8.4/10
Duration
Self-paced
Classes
8
This course will teach you the techniques used by real data scientists in the tech industry - and prepare you for a move into this hot career path.
Data Science and Machine Learning with Python - Hands On! is a self-paced Skillshare course focused on deep learning. It teaches learners to build and train neural networks with Python, apply deep learning to classification tasks, implement Convolutional and Recurrent Neural Networks (CNNs and RNNs) from scratch, and deploy models to production. The course serves individuals aiming to acquire practical, industry-relevant data science skills for a career in tech, using tools like TensorFlow.
What you'll learn in Data Science and Machine Learning with Python - Hands On!
Our Review of Data Science and Machine Learning with Python - Hands On!
The structure of Data Science and Machine Learning with Python - Hands On! is concise, with only three listed curriculum chapters covering an introduction, real-world classification, and a summary with career pathways. This suggests a streamlined, project-oriented approach rather than a comprehensive theoretical deep dive. The teaching format is self-paced video instruction typical of Skillshare, emphasizing hands-on implementation as indicated by the title and outcomes. The depth appears to be applied and technical, focusing on building specific network types and deployment, which implies a moderate to advanced difficulty level suitable for those with some prior programming or foundational knowledge stepping into deep learning.
The outcomes and curriculum indicate a learner who completes this course should be able to construct neural networks, CNNs, and RNNs programmatically and handle a model deployment pipeline. The value is tied directly to the Skillshare Premium subscription model at $13.99 per month, which provides access to this and other courses but does not include a verified certificate of completion. This makes it a cost-effective, ongoing learning resource for skill-building rather than a credential for formal validation. The course's strength is its practical, production-focused promise, but its brevity means foundational concepts may be covered quickly.
Pros and cons of Data Science and Machine Learning with Python - Hands On!
Pros
- Focuses on hands-on, practical implementation of deep learning models
- Covers in-demand production skills like model deployment with TensorFlow
- Outcomes target real-world classification tasks and building CNNs/RNNs from scratch
- Cost-effective access via affordable Skillshare Premium subscription
Things to consider
- No certificate of completion is indicated for credentialing
- Requires a Skillshare membership as a prerequisite
- The three-chapter curriculum suggests a condensed scope that may move quickly
Who should take Data Science and Machine Learning with Python - Hands On!?
This course is best for aspiring data scientists or software developers with some Python experience who want a practical, project-focused introduction to building and deploying deep learning models. It fits learners seeking hands-on skill development for industry applications over theoretical depth, and who value the affordability and breadth of a Skillshare subscription.
Course curriculum for Data Science and Machine Learning with Python - Hands On!
Data Science and Machine Learning with Python - Hands On! at a glance
| Provider | Skillshare |
|---|---|
| Instructor | Skillshare Instructor |
| Level | Intermediate |
| Time to complete | Self-paced |
| Pricing | Skillshare Premium ($13.99/mo) |
| Certificate | No |
| Prerequisites | Skillshare membership |
Fit
Best for
Not ideal for
The bottom line on Data Science and Machine Learning with Python - Hands On!
Data Science and Machine Learning with Python - Hands On! offers a pragmatic, applied entry into deep learning implementation and deployment, delivering good value for Skillshare subscribers focused on building job-ready skills, though it lacks a formal credential and assumes a learner is ready for hands-on coding.
Data Science and Machine Learning with Python - Hands On!: frequently asked questions
What is the Data Science and Machine Learning with Python - Hands On! course primarily about?
This Skillshare course is primarily about practical deep learning, teaching you to build neural networks, CNNs, and RNNs with Python and TensorFlow, apply them to classification tasks, and deploy models to production environments.
What prerequisites or difficulty level should I expect for this machine learning course?
The prerequisite is a Skillshare membership. The curriculum and outcomes, which include implementing networks from scratch and deployment, suggest a moderate to advanced difficulty suitable for learners with some foundational programming or data science knowledge.
Does this course provide a certificate and how does the pricing work?
No certificate of completion is indicated. Pricing is through a Skillshare Premium subscription, which costs $13.99 per month and grants access to this course and the platform's full library.
How can I get the most out of the Data Science and Machine Learning with Python - Hands On! course?
To get the most from this course, ensure you have a comfortable grasp of Python, actively code along with the hands-on projects, and practice applying the taught techniques to your own classification and deployment scenarios.