Foundational Maths and AI: Unlocking the Power to Push the Boundaries of Innovation

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Maths for AI Course Overview


Maths for AI is a course designed to prepare students for the mathematical challenges involved in tackling artificial intelligence problems. It provides a comprehensive overview of the mathematics necessary to solve problems related to AI, such as optimization, linear algebra, probability, and statistics. The course covers principles of machine learning, neural networks, and big data, as well as deep learning applications. Core topics in this course include data processing and analysis, supervised and unsupervised learning, univariate and multivariate linear regression, optimization and convex optimization, deep learning, and decision trees. The skills and abilities acquired through this course will enable students to better understand and evaluate the algorithms used in AI and enable them to develop, debug, and maintain high-quality software in the field.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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Get 1on-1 session with our expert trainers at a date & time of your convenience.
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Flexible Dates

Start your session at a date of your choice-weekend & evening slots included, and reschedule if necessary.
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4-Hour Sessions

Training never been so convenient- attend training sessions 4-hour long for easy learning.
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Destination Training

Attend trainings at some of the most loved cities such as Dubai, London, Delhi(India), Goa, Singapore, New York and Sydney.
Live Online Training (Duration : 36 Hours) Fee On Request
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.

4 Hours
8 Hours
Week Days
Weekend

Start Time : At any time

12 AM
12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Group Training
Date On Request
Course Prerequisites


Most AI courses don't require any specific math prerequisites, although having a working knowledge of linear algebra, calculus and statistics is helpful. The more math background the better, but these specific subjects are not necessarily essential.

Target Audience

The target audience for Mathematics for AI training would be people from a variety of backgrounds including software engineers, data scientists and those with a technical background. However, the course could also be suitable for general students looking to develop a better understanding or knowledge of the principles and fundamentals of AI, as well as professionals in fields such as finance, retail and health care who may wish to develop their skills in AI and use it in their business. The course is designed with a particular focus on the practical application of mathematical concepts as they relate to AI; this means that all students, regardless of their level of knowledge of mathematics, should be able to benefit from the course. In addition, the course should provide a clear and straightforward roadmap for those who wish to pursue further studies in AI and mathematics.

 

Learning Objective of Maths for AI:

1. Learn basic numbers and operations: Familiarize yourself with the fundamentals of math such as addition, subtraction, multiplication, division, and exponents.
2. Analyze data using statistics and probability: Understand the basics of probability and statistics, and how to use them to interpret data.
3. Work with equations and functions: Practice working with linear and quadratic equations, polynomials, and other types of equations.
4. Understand algorithms: Learn arithmetic and logic algorithms, including sorting algorithms, dynamic programming, and heuristics.
5. Develop a deeper understanding of AI: Develop a better understanding of how AI algorithms work and how to apply a number of AI techniques.
6. Learn vector and matrix calculations: Grasp the basics of vectors and matrices, and understand how to use them to solve equations.
7. Analyze data sets with calculus: Use calculus to analyze data sets and solve differential equations.
8. Employ optimization techniques: Employ optimization techniques, like linear programming and gradient descent, to solve different problem sets.

 

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FAQ's


Yes, fee excludes local taxes.
Yes, we do.
Schedule for Group Training is decided by Koenig. Schedule for 1-on-1 is decided by you.
In 1 on 1 Public you can select your own schedule, other students can be merged. Choose 1-on-1 if published schedule doesn't meet your requirement. If you want a private session, opt for 1-on-1 Private.
Duration of Ultra-Fast Track is 50% of the duration of the Standard Track. Yes(course content is same).
1-on-1 Public - Select your start date. Other students can be merged. 1-on-1 Private - Select your start date. You will be the only student in the class.
Yes, course requiring practical include hands-on labs.
You can buy online from the page by clicking on "Buy Now". You can view alternate payment method on payment options page.
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We use the best standards in Internet security. Any data retained is not shared with third parties.
You can request a refund if you do not wish to enroll in the course.
To receive an acknowledgment of your online payment, you should have a valid email address. At the point when you enter your name, Visa, and other data, you have the option of entering your email address. Would it be a good idea for you to decide to enter your email address, confirmation of your payment will be emailed to you.
After you submit your payment, you will land on the payment confirmation screen. It contains your payment confirmation message. You will likewise get a confirmation email after your transaction is submitted.
We do accept all major credit cards from Visa, Mastercard, American Express, and Discover.
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Yes, we do offer corporate training More details
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Yes, we also offer weekend classes.
Yes, Koenig follows a BYOL(Bring Your Own Laptop) policy.
It is recommended but not mandatory. Being acquainted with the basic course material will enable you and the trainer to move at a desired pace during classes. You can access courseware for most vendors.
Yes, this is our official email address which we use if a recipient is not able to receive emails from our @koenig-solutions.com email address.
Buy-Now. Pay-Later option is available using credit card in USA and India only.
You will receive the digital certificate post training completion via learning enhancement tool after registration.
Yes you can.
Yes, we do. For details go to flexi
You can pay through debit/credit card or bank wire transfer.
Dubai, London, Sydney, Singapore, New York, Delhi, Goa, Bangalore, Chennai and Gurugram.
Yes you can request your customer experience manager for the same.
Yes of course. 100% refund if training not upto your satisfaction.

Prices & Payments

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Travel and Visa

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Food and Beverages

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