How to learn Machine Learning and Artificial intelligence

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In this video we give a detailed road-map for learning Machine Learning and Artificial Intelligence.
*About us*

Applied AI course (AAIC Technologies Pvt. Ltd.) is an Ed-Tech company based out in Hyderabad offering on-line training in Machine Learning and Artificial intelligence. Applied AI course through its unparalleled curriculum aims to bridge the gap between industry requirements and skill set of aspiring candidates by churning out highly skilled machine learning professionals who are well prepared to tackle real world business problems.

*Key highlights of Applied AI course*

1. Job guarantee or money back guarantee
2. Query resolution inside 24 hours
3. Personalized learning path for every course participant
4. 30 Practical Assignments
5. 15 end-to-end case studies based on real world problems across various industries
6. Mentor-ship for portfolio development, resume and interview preparation, and career counseling for every course participant

For More information Please visit

For any queries you can either drop a mail to or call us at +91 8106-920-029 or +91 6301-939-583




Abhinav's Space says:

Summary of above video:
How to learn ML & AI:
– Learn theory and practical aspects
– Gain a good intuition on each concept
– Practice, Practice and Practice
– Understand boundary and practice
– easy, 5-10 hours a week for 3-6 months

1. Python: Learning Python, Mark Lutz, Python for Data Analysis – WestMckinney
2. Probability and Statistics: Think Stats, Khan academy course
3. Linear Algerbra: Gilbert Strang, Khan Academy course
4. Calculus: Multivariable Calculus Khan Academy, Convex Optimization -Stephen Boyd
5. Classification,Regression, Clustering and Matrix Factorizing, Dimensional Reduction: Machine Learning – Andrew Ng,
Pattern Recognition and Machine Learning – Christopher Bishop
6. Neural Network & Deep Learning: Deep learning specialization, DL by IAN goodfellow

For each technique learn:

1. Math
2. Geometric intuition
3. Assumptions
4. Best and Worst Case
5. Interoperability
6. Outliers
7. Skewed/Biased dataset
8. Code
9. Variations
10. Limitations and Workarounds


Problem solving
– solve problems end to end
– understand why a technique is working or not
– document/code(github/blog)
– build a portfolio (5+ case studies – thorough analysis)
– read other's blogs or code

kazi MRahman says:


Carlos Ortiz says:

Thank you for this information

saurabh tripathi says:

Please include case studies in BFSI domain as well. Also will one be able to clear CAP certification after doing this course?

Devain Pal Bansal says:

can you recommend any books to go through for the machine learning algorithms, like decision trees etc. that too with the mathematics behind them.

Rahul Kumar sharma says:

Hi,,I wnat to do the course but no one is picking call,,,wht to do ?

Zeeshan Ahmad says:

simply great what's the name of great teacher .

krishna prasad says:

I love it. I love your presentation with bullet points. Finally it's cleared my myths about ML. Thanks a lot.

venkat b says:

Hi, anybody enrolled & completed ! They charging $500. Just would like to know. Thanks.

Vishwanath Biswal says:

wow sir ..,
So amazing you are !
Thank you so much for sharing this information , it really helps me a lot .

Ahmed El-Sabagh says:

Thanks very much I appreciate your effort in this video

Devesh Maheshwari says:

Loving vedio

rahul RD says:

dear sir,
thanks for above. i want to do start up in AI.can you please guide me and be my mentor..?

yugandhar reddy says:

Who thing having machine learning skill going to get paid a lot of package ….don't dream about big packages these body shop MNC's will not gonna give more then 7lpa even u have 4 yrs experience. Machine learning buzzing a lot these days …once hadoop also trended a lot ..every body learned hadoop after 12 month of hadoop hype most of people left big data hadoop coz of less call


Sir you are telling some videos are free ..means for others we have to paid?!!!

sahil mohammed says:

good video. one suggestion is lot of time is spent on repeating same thing again and again in one way or the other. references to books/websites, introduction about the topics coverd , strategy etc can be crisp and quick

rakzr says:

What's the prospect of Machine learning? As I searched for jobs over indeed there's hardly any company offering jobs for Fresher. And even after 3-4 years of experience they're providing around 6lpa and that's not really to aspire for.
Moreover, should I go for Post grad and PhD or can I just get my career a push right after my Undergrad completion?

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