SKU: 11081732152

1998-2013 VW GOLF 1.4T 1.6FSI 1.4 55KW/59KW 4x Coil Packs Set 036905715F

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Description

1998-2013 VW GOLF 1.4T 1.6FSI 1.4 55KW/59KW 4x Coil Packs Set 036905715F4x VW Golf 1. 4 TSI VW Polo Jetta 1. 6 FSI Tiguan Coil Packs Set 036905715F Feature: 1: According to the original factory specifications,perfect match for the original car. 2: Own different test machines to design exact accurate parameter for our products. All items were tested for performance. 3: Made by high quality material, lightweight, anti rust, colorfast and durable. 4: Aftermarket product with premium quality. 5: Stable performance, high

4x VW Golf 1.4 TSI VW Polo Jetta 1.6 FSI Tiguan Coil Packs Set 036905715F

Feature:
1: According to the original factory specifications,perfect match for the original car.
2: Own different test machines to design exact accurate parameter for our products.All items were tested for performance.
3: Made by high quality material, lightweight, anti-rust, colorfast and durable.
4: Aftermarket product with premium quality.
5: Stable performance, high reliability,suitable for replacing your broken one.

Specifics:
Condition: New
Material:Metal
Color:show as pictures
Manufacturer Part Number:036905100 , 036905100A , 036905100B, 036905100C , 036905100D , 036905715, 036905715A , 036905715C ,036905715E, 036905715F , 036905715G
Interchange Part Number:036905715F , 036905715G
Other Part Number:036905715F
Type:Ignition Coil
Connector Type: 6 Pin
Placement on Vehicle:Front, Left, Rear, Right
Fitment Type:Direct Replacement

Reference OE/OEM Number:
036905100 , 036905100A , 036905100B
036905100C , 036905100D , 036905715
036905715A , 036905715C , 036905715E
036905715F , 036905715G,036 905 100 A
036 905 100 B,036 905 715,036 905 715 A
036 905 100 C

Fitment:
For VW：
For VW BEETLE 2002-2016 1.4T 1.4 55KW
For VW CADDY 2004-2011 1.4 55KW/59KW
For VW CC 2009-2016 1.4T
For VW EOS 2006-2016 1.6FSI 1.4T
For VW GOLF 1998-2013 1.4T 1.6FSI 1.4 55KW/59KW
For VW GOLF PLUS 2005-2014 1.6FSI 1.4 55KW/59KW 1.4T
For VW BORA 1999-2005 1.4 55KW 1.6FSI
For VW JETTA 2006-2016 1.4T 1.6FSI PASSAT 2006-2015 1.4T 1.6FSI
For VW POLO 2002-2016 1.4 1.4T
For VW SCIROCCO 2009-2016 1.4T
For VW SHARAN 2011-2016 1.4T
For VW TIGUAN 2008-2016 1.4T
For VW TOURAN 2003-2015 1.6FSI 1.4T
For VW LUPO 1999-2006 1.4 55KW

For Audi：
For AUDI A1 2011-2014 1.4T
For AUDI A2 2000-2005 1.4 55KW
For AUDI A3 2004-2013 1.6FSI 1.4T

For Seat：
For Seat ALHAMBRA 2011-2015 1.4T
For Seat ALTEA 2007-2015 1.4 63KW 1.4T
For Seat IBIZA 2002-2015 1.4 74KW 1.2 1.4 55KW
For Seat LEON 2002-2013 1.6FSI 1.4 55KW
For Seat TOLEDO 2002-2015 1.6FSI 1.4 55KW/63KW
For Seat CORDOBA 2003-2009 1.4 73KW/55KW/74KW 1.6FSI 1.4 63KW

For Skoda：
For Skoda FABIA 2000-2015 1.4 55KW/63KW/74KW
For Skoda OCTAVIA 2001-2013 1.4 55KW/59KW 1.6FSI
For Skoda RO0MSTER 2006-2015 1.4
For Skoda SUPERB 2008-2015 1.4T
For Skoda YETI 2010-2016 1.4T

Package Include:
4x Ignition Coil

Note:
1.Please check the description or use the year/make/model check finder and replace part numbers to confirm the compatibility before purchasing.
2.Professional installation is recommended.

Warranty:

Returns: Customers have the right to apply for a return within 60 days after the receipt of the product
24-Hour Expert Online: Solve your installation and product problems

Shipping Notes
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Exchange/Return Notes
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SKU: 11081732152

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4.7 ★★★★★
Based on 9 reviews
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Product Reviews
S
Verified Purchase
Shannon
Grantham, US
★★★★★ 5
The best DL/ML book I have ever seen!!
Format: Hardcover
Fantastic deep-learning book! The logic is very easy to follow, but the content is very thorough when it comes to explaining the theories behind it, making it perfect for beginners as well as math and CS students. The best DL/ML book I have ever seen!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 30, 2025
W
Verified Purchase
William P Ross
Birmingham, US
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning. There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s. The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read. There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning. The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique. Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Battle Creek, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Dallas, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 14, 2017
M
Verified Purchase
mackster
Alexandria, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 15, 2018

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