Logistic regression
In this project, the students are expected to perform the "Logistic Regression Algorithm" taught in the course based on the given input data.
Computer Science · Course
Math behind Machine Learning & Artificial Intelligence using Python
Lay a strong foundation in basic math concepts required for building algorithms with the artificial intelligence and machine learning course. Our extensive training will help you to develop competent skills essential for the era of AI and ML.
- Duration
- 12 weeks
- Content
- 25 hours
- Projects
- 2
- Mode
- Online
OverviewWhat you'll
What you'll
be able to do.
- Extension of machine learning course
- Understanding of Mathematics behind different machine learning algorithms such as linear regression, principal component analysis etc
- This course is very important if someone want to learn deep learning
- This course also involves lot of Mathematics with pen and paper
Tools you'll use
Python
Curriculum12 modules,
Get the full syllabus ↓12 modules,
built with industry.
01Math behind Machine Learning & Artificial Intelligence using Python
- Week - 01 Basic conceptsW01
- In this session, we will learn about
- Sets
- Subsets
- Power set
- Venn Diagrams
- Trigonometric Functions
- Straight lines
- A.M, G.M, and H.M
- Concepts of Vectors
- In this session, we will learn about
- Week - 02 Permutation & CombinationsW02
- In this week's session, we will learn about:
- Introduction to permutation and combinations
- Basics of permutation and combinations
- Fundamental principle of counting
- Permutations
- Combinations
- In this week's session, we will learn about:
- Week - 03 Statistics - IW03
- In this week's session, we will learn about:
- First business moment
- Second business moment
- Third business moment
- Fourth business moment
- In this week's session, we will learn about:
- Week - 04 ProbabilityW04
- In this week's session, we will learn about:
- Introduction to probability
- Random experiments
- Conditional probability
- Joint probability
- In this week's session, we will learn about:
- Week - 05 Statistics – IIW05
- In this week's session, we will learn about:
- Z Scores
- Confidence interval
- Correlation
- Covariance
- In this week's session, we will learn about:
- Week - 06 Probability - IIW06
- In this week's session, we will learn about:
- Introduction to probability - II
- Uniform Distribution
- Normal Distribution
- Binomial Distribution
- Poisson Distribution
- In this week's session, we will learn about:
- Week - 07 Likelihood (for Logistic regression)W07
- In this week's session, we will learn about:
- Introduction to likelihood statistics
- Odds
- Log odds
- Maximum likelihood vs probability
- Logistic regression
- In this week's session, we will learn about:
- Week - 08 Gradient descent (for Linear & Logistic regression)W08
- In this week's session, we will learn about:
- Loss function
- Cost function
- The gradient descent for linear regression
- The gradient descent for logistic regression
- In this week's session, we will learn about:
- Week - 09 Linear Algebra (for PCA)W09
- In this week's session, we will learn about:
- Matrices
- Types of matrices
- Operation on matrices
- Eigen values
- Eigen vectors
- In this week's session, we will learn about:
- Week - 10 Derivatives (for Neural network)W10
- In this week's session, we will learn about:
- Derivatives
- Intuitive ideas of derivatives
- Increasing & decreasing function
- In this week's session, we will learn about:
- Week - 11 Backpropagation (for Deep learning)W11
- In this week's session, we will learn about:
- Chain rule
- Maxima & minima
- Back propagation
- The cost function for deep learning
- In this week's session, we will learn about:
- Week - 12 PythonW12
- In this week's session, we will learn about:
- Basics of Python
- If else
- For loop
- Data types
- In this week's session, we will learn about:
- Week - 01 Basic conceptsW01
Industry projects2 projects
2 projects
you'll ship.
Our projects are designed by experts in the industry to reflect industry standards. By working through our projects, Learners will gain a practical understanding of what they will take on at a larger-scale in the industry. In total, there are 2 Projects that are available in this program.
Gradient descent
In this project, the students are expected to perform the gradient descent for ANN in Python based on the given input data.
FeeOne fee.
One fee.
Everything included.
Become job ready with our comprehensive industry focused curriculum for freshers & early career professionals
Premium
₹40,000
Inclusive of all charges- 1 Year Access
- Personalized Page
- Live Individual & Group Sessions
- Personalized & Hands-On
- Job-Oriented Industry Relevant Curriculum
FAQQuestions,
Questions,
answered.
Who can take up this Machine Learning crash course?
Students and graduates with a technical background in Computer Science can opt for this course.
Is this an online Machine Learning certification course?
Yes, this is a 100% online course.
What is Machine Learning?
Machine Learning is part of AI where the inanimate objects are programmed to behave like human beings. They slowly learn, and with experience and training, their accuracy increases.
What is the fee for this Machine Learning online course?
The fee structure is flexible, and you can choose a plan that suits you. The basic plan would give you two months of access, the pro plan would give you four months of access, and the premium plan would give you lifetime access.
How much can a machine learning engineer earn?
According to Glassdoor, the average salary of a machine learning engineer is INR 8 LPA. After completing this course, you can also earn this average pay, and you can expect more once you become an experienced professional.
Is there any certificate for completing this Math behind Machine Learning & Artificial Intelligence using Python course?
Yes, After completing this best Machine Learning course, you shall be given a course completion certificate. The top 5% of the scorers will be given a merit certificate alongside the course completion certificate.
Is there any technical support available for this Machine Learning course students?
Yes, you can clear your queries with email and forum support.
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