Journey Into Data/AI /Big Data — Chapter Two: DL/AI



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Journey Into Data/AI /Big Data — Chapter Two: DL/AI

So, on the journey to learning about the new, vast and relatively very interesting field of data and artificial intelligence, now comes the time to share with everyone the pathway to learn about the next step on it.
This phase is in direct correlation with the previous blog (https://nishantranjanverma.medium.com/journey-into-data-ai-big-data-chapter-one-8ad148f0caf9) I posted and is a prerequisite to go through learning it as well. Before studying deep learning and artificial intelligence, anyone needs to have an understanding of machine learning/mathematics/programming.

Deep Learning (including NLP,CV,TimeSeries) and Artificial Intelligence is next advance step in the direction of machine learning and data science. Students/Professional gaining knowledge and skillsets can easily scale
up to become a AI Engineer, Deep Learning Engineer, NLP Engineer and Computer Vision Engineer. That being mentioned it is very important to take time in not just practicing codes but also making up to the mark conceptual understanding of the subject.

I will share the courses which I followed and found very useful on learning the intricate knowledge associated with the subject. The courses related to python and mathematics are going to be the same as the previous blog.
But, I will mention them just so it gives a complete picture of the whole.

Major Combination Courses:

Course: Deep Learning Specialization by Andrew NG/Deeplearning.ai
Reviews: This course is being taught by one of the pioneer of the field, Andrew Ng. A well constructed combined course consisting 5 courses which puts you in perfect position in the field.
Also it is available for free if you don’t need the certification.
Links: https://www.coursera.org/specializations/deep-learning#courses

Course: AI Engineer Masters by Simplilearn/IBM
Reviews: Another massive yet highly rewarding course from simplilearn. You will be taught by industry experts in the live classes plus will have multiple courses like deep learning, nlp amongst others. It is developed
in coordination with IBM.
Links: https://www.simplilearn.com/artificial-intelligence-masters-program-training-course

Deep learning/AI:

Course: Complete Tensorflow 2 and Keras Deep Learning Bootcamp
Reviews: This another gem of a course by none other Jose Portilla. You will have enough knowledge and practice on the subject of deep learning by the time you will done with the course.
Links: https://www.udemy.com/course/complete-tensorflow-2-and-keras-deep-learning-bootcamp/

Course: Complete Deep Learning by Krish Naik
Reviews: Everything in relation to deep learning and similar studies can be found here. He knows where we as a learner might find it difficult to grasp a particular course.
Links: https://www.youtube.com/playlist?list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi

Course: MIT: Deep Learning Lectures
Reviews: One course from the college for technical education, MIT. And the it is for free to watch/study on youtube. What more can be asked?
Links: https://www.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI

Course: An Introduction to Artificial Intelligence by IIT Delhi
Reviews: A massive and highly course intesive. If you want to the ins and outs of AI, here is what you can look for. All the algorithms are explained in detail. Superb Course.
Links: https://www.youtube.com/watch?v=GHpchgLoDvI&list=PLp6ek2hDcoNB_YJCruBFjhF79f5ZHyBuz

Natural Language Processing (NLP):

Course: NLP — Natural Language Processing with Python
Reviews: Jose Portilla’s course on NLP should always be on your list if your are learning NLP.
Links: https://www.udemy.com/course/nlp-natural-language-processing-with-python/

Course: Natural Language Processing by Krish Naik
Reviews: NLP by Krish Naik is a superclass study place for all your doubts. Plus is on youtube then it is free. Concepts are just find more meaning while studying with him.
Links: https://www.youtube.com/playlist?list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Computer Vision (CV):

Course: Computer Vision by Standford University
Reviews: Again a premier university, ranked top many times. The faculties knowhow on the subject is just magnificient.
Links: https://www.youtube.com/playlist?list=PLf7L7Kg8_FNxHATtLwDceyh72QQL9pvpQ

Course: Python for Computer Vision with OpenCV and Deep Learning by Jose Portilla (Udemy)
Reviews: It will start exactly from ground on the field of image processing and it’s elements and all the way to the advance algorithms in the domains. Worth every minute of learning it here. Masterpiece!!!
Links: https://www.youtube.com/playlist?list=PLf7L7Kg8_FNxHATtLwDceyh72QQL9pvpQ

TimeSeries:

Course: Python for Time Series Data Analysis by Jose Portilla (Udemy)
Reviews: Simple and crisp at the same time. You know you are in right place when the concepts which may sound difficult start making sense instantly.
Links: https://www.udemy.com/course/python-for-time-series-data-analysis/

Mathematics for Deep Learning/Machine Learning:

Course: Mathematics for Machine Learning Specialization from Imperial College
Reviews: Very unique way of teaching and cutting down to the relevant areas of the course. Fun fact: It is also available on youtube for free minus the course downloadable stuff and quiz.
Link1: https://www.coursera.org/specializations/mathematics-machine-learning
Link2: https://www.youtube.com/watch?v=T73ldK46JqE&list=PLiiljHvN6z1_o1ztXTKWPrShrMrBLo5P3 (Youtube)

Python Programming:

Course: Modern Python 3 by Colt Steele
Reviews: This one guy who can make anything fun and interesting. His teaching methodology is very unique and makes you code in an instant. He also has a great SQL course which you may try if you like his style of teaching.
Links: https://www.udemy.com/course/the-modern-python3-bootcamp/

Here are few add on books, as mentioned the prerequisite is always to go through the books mentioned in the previous blog. These are 2 which I found covers almost majority of the topics in AI/Deep Learning. I have used the below 2 mentioned mostly for the quality of content and the style in which it was delivered. Hope you find them use full as well.

Books:

1. Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig.
Review: Well constructed and simple to understand. Filled with examples and practical code github repo.

2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron
Review: The author begins with the simple understanding to make you as proficient as possible by the end of the course through this highly recommended book.

Blogs and Youtube Channels are very important as they just not only provide us with update information but also some quick tricks for trivial subject matter.

Blogs/Youtube Channels

Blogs:

>> medium.com
>> towardsdatascience.com
>> machinelearningmastery.com
>> analyticsindiamag.com

Youtube:

>> 3Blue1Brown
>> Lex Fridman
>> Two Minute Papers

Towards the end of this blog, the one most important piece of advice which I encountered and still faces many a times, is to keep that in mind that this a highly advance field and most of the work is generated from years of research thus if there is no progress or you could not understand some parts, then that does not mean that you are not good enough/or not making progress. It is only that it takes time and once you will start making sense of the whole subject then everything will fine. So, just keep on learning and progressing on day to day basis. Very soon it all will fall in right places.

So, this was my part for the journey in the field of AI and Deep Learning. I will very soon publish the 3rd and final part which will give you the pathway for learning Big Data and will cherish/support your goal to become a Big Data Engineer.

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