Program profile · official sources
Deep Learning in Python
A PyTorch learning track for learners moving from traditional ML into deep-learning applications.
Commercial status: no commercial relationship is documented for this page. The verification link goes directly to the official provider source.
Who it is for
The narrative recommends familiarity with traditional machine learning, while the formal track prerequisite section says none. Both statements inform the learning-fit decision.
Who should skip it
Compare an ML foundation first if you are starting without that background, and consider the subscription model if you require a one-time purchase.
Facts checked 8 Sep 2026
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price
- Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. ·
- Provider link
See price and enroll at DataCamp (official site) ↗
Official site. No commission.
- Time
- 18 hours
- Level
- Beginner
- Credential
- Statement of Accomplishment
Add this credential to your LinkedIn profile, resume, or CV; share it on social media and in your performance review.
- Format
- Online self-paced learning track
- Prerequisites
- There are no prerequisites for this track
Sources ↗
Course and activity access
Career and Skill tracks: Not included / Included / Included (Basic / Premium / Teams).. Official source
What you actually do
Five courses and one bonus project address neural-network building and training through image classification, time-series prediction, NLP and Transformers. The beginner label does not erase the narrative's recommendation for traditional ML familiarity. It also does not establish a mandatory prior course that the formal prerequisite section does not require.
The framework and application choices provide a useful starting point for comparison. This track works with PyTorch across several kinds of data, while another deep-learning route may use TensorFlow or organise practice differently. Decide whether you need an introduction to deep learning built on existing ML familiarity or a different foundation first.
The formal no-prerequisites statement should remain visible alongside the narrative recommendation. It does not require inventing an admission test, nor does it make your current familiarity irrelevant to the learning decision. Review the neural-network and application scope against the work you want to practise.
Before you start
There are no prerequisites for this track
Curriculum
The deep-learning track's 18-hour content estimate is kept separate from elapsed study and subscription periods. Course and project notes remain intact where normalized duration fields do not supply a complete comparable allocation.
| Entry | Subject | Listed time | Share | Role | Observed |
|---|---|---|---|---|---|
| 1 | Introduction to Deep Learning with PyTorch | Not stated | Not calculated | Course; provider-listed track item. | 2026-09-08 |
| 2 | Intermediate Deep Learning with PyTorch | Not stated | Not calculated | Course; provider-listed track item. | 2026-09-08 |
| 3 | Building an E-Commerce Clothing Classifier Model | Not stated | Not calculated | Bonus project | 2026-09-08 |
| 4 | Deep Learning for Images with PyTorch | Not stated | Not calculated | Course; provider-listed track item. | 2026-09-08 |
| 5 | Deep Learning for Text with PyTorch | Not stated | Not calculated | Course; provider-listed track item. | 2026-09-08 |
| 6 | Transformer Models with PyTorch | Not stated | Not calculated | Course; provider-listed track item. | 2026-09-08 |
US price
| Purchase information | Recorded terms |
|---|---|
| Access and billing | As observed in the United States on 2026-09-08, USD35 buys one regular month of DataCamp Premium access. The listed track duration does not establish a required number of paid months or a guaranteed total cost to finish. A complete third-party budget and checkout tax treatment are not established in the price observation. |
| Refund and retakes | Refund and retake terms are not established in these stored policy fields. |
Alternatives
DeepLearning.AI's Coursera specialisation adds a non-paying-provider comparison. Its expected Python preparation and TensorFlow-based work differ from the PyTorch route here; read those requirements before selecting by the shared deep-learning title alone. It can help to choose a concrete learning objective, such as understanding a neural-network application you expect to work on. That objective should guide the framework and preparation comparison, without turning a listed project into a promise of professional expertise or a guaranteed result.
Deep Learning Specialization
| Provider and format | Level | Workload | Award | US price observation |
|---|---|---|---|---|
| DeepLearning.AI · 100% online, self-paced course | Intermediate level | Overview: 3 months at 10 hours a week. FAQ: at 5 hours a week, each course typically takes 5 weeks except course 3, which takes about 4 weeks. These are separate provider estimates; no combined completion promise is inferred. | Provider-issued certification | As shown in the United States on 28 September 2026: No specific total price is stated. Subscription is required for full access. Financial aid is available. No numeric course-completion total or ISO currency is established from the saved page. |
| Entry and assessment questions | Recorded answer |
|---|---|
| Who is it aimed at? | Early-career software engineers or technical professionals looking to master fundamental concepts and gain practical machine learning and deep learning skills. |
| What preparation is required? | Learners should have intermediate Python experience (e.g., basic programming skills, understanding of for loops, if/else statements, data structures such as lists and dictionaries). Recommended: basic knowledge of linear algebra (matrix-vector operations and notation) and machine learning concepts (how to represent data, what an ML model does, etc.). |
| How is the award earned? | Complete all courses and the applied learning projects. |
| What remains unconfirmed? | Expiry, renewal, and retake conditions are not explicitly established. |
Official source · 2026-10-15 | Official source · 2026-09-28
Speech Recognition with Python
| Provider and format | Level | Workload | Award | US price observation |
|---|---|---|---|---|
| 365 Data Science · 100% online, self-paced course | Intermediate | 3 hours (provider headline; module and exam timings listed separately) | Provider-issued course certificate | As shown in the United States on 3 October 2026, the 365 pricing page Self-study card displays $36/month reference price and a $29/month price billed annually; the same pricing page FAQ separately states $29/month full access. USD is explicit in the saved pricing page state. These are platform access quotes, not a course-completion total. Certificates are included with Self-study. |
| Entry and assessment questions | Recorded answer |
|---|---|
| Who is it aimed at? | Tailored for data analysts, scientists, audio engineers, AI enthusiasts, and anyone with a curious mind. |
| What preparation is required? | Python (version 3.8 or later), SpeechRecognition and PyAudio libraries, and a code editor or IDE (e.g., Jupyter Notebook, Spyder, or VS Code). Basic understanding of Python programming is required. No prior experience with audio processing or speech recognition is necessary. Advanced preparation: Introduction to Python, Machine Learning in Python. |
| How is the award earned? | Complete the course and pass its course exam with 60% or above under the general certificate terms. Certificates are included with the Self-study learning plan. |
| What remains unconfirmed? | Expiry, renewal, and retake conditions are not explicitly established. CPE credit acceptance depends on individual state boards. |
Questions before enrolling
What completion record can I earn, and are separate exam conditions established?
Finishing the required materials earns a DataCamp Statement of Accomplishment that can be shared on professional profiles. An exact assessment condition, separate exam requirement, expiry and renewal are not established in the reviewed record dated 8 September 2026.
Change log
- : Initial review of official program, curriculum, credential and subscription-access sources. · Source