Mathematics for Emerging Pathways
Unlike the popular belief, mathematics is greatly invigorating and tirelessly comprehensible. If you intend to have a career in any STEM field, but you are afraid of the numbers and are intimidated by strange looking symbols, then this course will be the perfect start point for you. The course is suitable for learners with intermediate or Alevels qualification who intend to have a career in the emerging technologies such as data science, machine learning and artificial intelligence. This course will also be extremely useful for those who already know the computation procedures but lack the deep insight of the mathematical concepts.
Dr Awais
Trainer
I have a PhD in electrical engineering and my primary area of research is in control systems, optimization, robotics and Artificial Intelligence.
4 Courses
Mathematics for Emerging Pathways
Unlike the popular belief, mathematics is greatly invigorating and tirelessly comprehensible. If you intend to have a career in any STEM field, but you are afraid of the numbers and are intimidated by strange looking symbols, then this course will be the perfect start point for you. The course is suitable for learners with intermediate or Alevels qualification who intend to have a career in the emerging technologies such as data science, machine learning and artificial intelligence. This course will also be extremely useful for those who already know the computation procedures but lack the deep insight of the mathematical concepts.
Dr Awais
Trainer
I have a PhD in electrical engineering and my primary area of research is in control systems, optimization, robotics and Artificial Intelligence.
4 Courses
Languages Available:  English  Urdu 
No. of Courses :  04 
Rating :  waiting 
Reviews :  waiting 
Students Enrolled :  waiting 
About This Course
Mathematics for Emerging Pathways is intended to provide the learners with the essential basis for becoming data, machine learning and artificial intelligence experts. Unlike many other online courses on data science and machine learning that focus on the use of some software tools or existing algorithms, this course is designed to emphasize that Whether you like it or not, data science should always be about the science (not data), and following that thread, mathematical tools and techniques become indispensable.
What you will learn
We will learn the fundamental mathematics concepts that undercut the advanced technologies such as robotics, data science, artificial intelligence etc. Specifically, we will learn:

Linear Algebra – Matrix theory and its real world applications
 Linear systems
 Vectors and vector spaces
 Linear transformations
 Composition of transformation
 Eigenvalues and Eigenvectors

Probability – as a tool for decision making under uncertain circumstances
 Basic notions
 Joint, Conditional, marginal probability, posterior probability
 Discrete probability distributions
 Continuous probability distributions

Statistics
 Descriptive statistics
 Inferential Statistics
Calculus and Optimization
 Single variable derivative
 Partial derivative
 Gradient
 Gradient descent
What skills you will gain

 Develop mathematical model of linear systems
 Solving system of linear equations and understanding its geometry
 Geometry of linear equations

 Application of mathematics to real world problems
 Analytical and computation skills in the topics covered

 Understand the mathematics and geometry of optimization
 Ability to use descriptive and inferential statistics for decision making for different types of underlying distributions
Earning Potentials
The global business value derived from data related technologies such as analytics, machine learning and Artificial Intelligence (AI) is projected to reach over around $50 trillion by 2030. This course will enable you to join the club of highest earners in your respective fields.
Course Delivery Mode
The training will be delivered online via our alnafi.com portal, which is designed to cater 50 Million Nafi members. The portal has all the key features like: Watching and tracking videos
 Progress monitoring,
 Attempting quizzes,
 Submitting assignments,
 Asking questions from the teachers and mentors
Course Curriculum
Part 1  Linear Algebra
 Introduction to Linear Algebra
 Introduction to Linear Algebra
 Vectors
 Matrices
Part 2  Probability and Random Variable
 Probability
 Random Variables
Part 3  Statistics and Hypothesis Testing
 Descriptive Statistics
 Inferential Statistics
 Regression
Part 4  Calculus
 Derivatives
 Optimization
 Partial Derivatives
Part 1  Linear Algebra
 Introduction to Linear Algebra
 Introduction to Linear Algebra
 Vectors
 Matrices
Part 2  Probability and Random Variable
 Probability
 Random Variables
Part 3  Statistics and Hypothesis Testing
 Descriptive Statistics
 Inferential Statistics
 Regression
Part 4  Calculus
 Derivatives
 Optimization
 Partial Derivatives