Probability

Spring 2025
#29108
EECS 126 107D - DIS 107D offered through Electrical Engineering and Computer Sciences

Probability and Random Processes

Jan 21, 2025 - May 09, 2025
We
01:00 pm - 01:59 pm
Dwinelle 205
Class #:29108
Units:4

Instruction Mode: In-Person Instruction

Time Conflict Enrollment Allowed

No Open Seats
EECS 126 - DIS 107D Probability and Random Processes more detail
This course covers the fundamentals of probability and random processes useful in fields such as networks, communication, signal processing, and control. Sample space, events, probability law. Conditional probability. Independence. Random variables. Distribution, density functions. Random vectors. Law of large numbers. Central limit theorem. Estimation and detection. Markov chains.
Spring 2025
#29105
EECS 126 106D - DIS 106D offered through Electrical Engineering and Computer Sciences

Probability and Random Processes

Jan 21, 2025 - May 09, 2025
Fr
11:00 am - 11:59 am
Hearst Gym 242
Class #:29105
Units:4

Instruction Mode: In-Person Instruction

Time Conflict Enrollment Allowed

No Open Seats
EECS 126 - DIS 106D Probability and Random Processes more detail
This course covers the fundamentals of probability and random processes useful in fields such as networks, communication, signal processing, and control. Sample space, events, probability law. Conditional probability. Independence. Random variables. Distribution, density functions. Random vectors. Law of large numbers. Central limit theorem. Estimation and detection. Markov chains.
Spring 2025
#29091
EECS 126 105D - DIS 105D offered through Electrical Engineering and Computer Sciences

Probability and Random Processes

Jan 21, 2025 - May 09, 2025
Fr
02:00 pm - 02:59 pm
Evans 9
Class #:29091
Units:4

Instruction Mode: In-Person Instruction

Time Conflict Enrollment Allowed

No Open Seats
EECS 126 - DIS 105D Probability and Random Processes more detail
This course covers the fundamentals of probability and random processes useful in fields such as networks, communication, signal processing, and control. Sample space, events, probability law. Conditional probability. Independence. Random variables. Distribution, density functions. Random vectors. Law of large numbers. Central limit theorem. Estimation and detection. Markov chains.
Spring 2025
#29090
EECS 126 104D - DIS 104D offered through Electrical Engineering and Computer Sciences

Probability and Random Processes

Jan 21, 2025 - May 09, 2025
We
04:00 pm - 04:59 pm
Stanley 179
Class #:29090
Units:4

Instruction Mode: In-Person Instruction

Time Conflict Enrollment Allowed

Open Seats

32 Unreserved Seats

EECS 126 - DIS 104D Probability and Random Processes more detail
This course covers the fundamentals of probability and random processes useful in fields such as networks, communication, signal processing, and control. Sample space, events, probability law. Conditional probability. Independence. Random variables. Distribution, density functions. Random vectors. Law of large numbers. Central limit theorem. Estimation and detection. Markov chains.
Spring 2025
#29059
EECS 126 103D - DIS 103D offered through Electrical Engineering and Computer Sciences

Probability and Random Processes

Jan 21, 2025 - May 09, 2025
We
03:00 pm - 03:59 pm
Latimer 102
Class #:29059
Units:4

Instruction Mode: In-Person Instruction

Time Conflict Enrollment Allowed

No Open Seats
EECS 126 - DIS 103D Probability and Random Processes more detail
This course covers the fundamentals of probability and random processes useful in fields such as networks, communication, signal processing, and control. Sample space, events, probability law. Conditional probability. Independence. Random variables. Distribution, density functions. Random vectors. Law of large numbers. Central limit theorem. Estimation and detection. Markov chains.
Spring 2025
#29058
EECS 126 102D - DIS 102D offered through Electrical Engineering and Computer Sciences

Probability and Random Processes

Jan 21, 2025 - May 09, 2025
We
11:00 am - 11:59 am
Social Sciences Building 136
Class #:29058
Units:4

Instruction Mode: In-Person Instruction

Time Conflict Enrollment Allowed

No Open Seats
EECS 126 - DIS 102D Probability and Random Processes more detail
This course covers the fundamentals of probability and random processes useful in fields such as networks, communication, signal processing, and control. Sample space, events, probability law. Conditional probability. Independence. Random variables. Distribution, density functions. Random vectors. Law of large numbers. Central limit theorem. Estimation and detection. Markov chains.
Spring 2025
#29057
EECS 126 101D - DIS 101D offered through Electrical Engineering and Computer Sciences

Probability and Random Processes

Jan 21, 2025 - May 09, 2025
We
10:00 am - 10:59 am
Hearst Field Annex B1
Class #:29057
Units:4

Instruction Mode: In-Person Instruction

Time Conflict Enrollment Allowed

No Open Seats
EECS 126 - DIS 101D Probability and Random Processes more detail
This course covers the fundamentals of probability and random processes useful in fields such as networks, communication, signal processing, and control. Sample space, events, probability law. Conditional probability. Independence. Random variables. Distribution, density functions. Random vectors. Law of large numbers. Central limit theorem. Estimation and detection. Markov chains.
Spring 2025
#29056
EECS 126 001 - LEC 001 offered through Electrical Engineering and Computer Sciences

Probability and Random Processes

Kannan Ramchandran
Jan 21, 2025 - May 09, 2025
Tu, Th
02:00 pm - 03:29 pm
Lewis 100
Class #:29056
Units:4

Instruction Mode: In-Person Instruction

Open Seats

40 Unreserved Seats

EECS 126 - LEC 001 Probability and Random Processes more detail
This course covers the fundamentals of probability and random processes useful in fields such as networks, communication, signal processing, and control. Sample space, events, probability law. Conditional probability. Independence. Random variables. Distribution, density functions. Random vectors. Law of large numbers. Central limit theorem. Estimation and detection. Markov chains.
Spring 2025
#27636
DATA C140 114S - SUP 114S offered through Data Science Undergraduate Studies

Probability for Data Science

Andrew Thein
Jan 21, 2025 - May 09, 2025
Fr
01:00 pm - 01:59 pm
Physics Building 3
Class #:27636
Units:4

Instruction Mode: In-Person Instruction

No Open Seats
DATA C140 - SUP 114S Probability for Data Science more detail
An introduction to probability, emphasizing the combined use of mathematics and programming. Discrete and continuous families of distributions. Bounds and approximations. Transforms and convergence. Markov chains and Markov Chain Monte Carlo. Dependence, conditioning, Bayesian methods. Maximum likelihood, least squares prediction, the multivariate normal, and multiple regression. Random permutations, symmetry, and order statistics. Use of numerical computation, graphics, simulation, and computer algebra.
Spring 2025
#27635
DATA C140 113S - SUP 113S offered through Data Science Undergraduate Studies

Probability for Data Science

Nic Sebastian Ross
Jan 21, 2025 - May 09, 2025
Fr
12:00 pm - 12:59 pm
Physics Building 3
Class #:27635
Units:4

Instruction Mode: In-Person Instruction

No Open Seats
DATA C140 - SUP 113S Probability for Data Science more detail
An introduction to probability, emphasizing the combined use of mathematics and programming. Discrete and continuous families of distributions. Bounds and approximations. Transforms and convergence. Markov chains and Markov Chain Monte Carlo. Dependence, conditioning, Bayesian methods. Maximum likelihood, least squares prediction, the multivariate normal, and multiple regression. Random permutations, symmetry, and order statistics. Use of numerical computation, graphics, simulation, and computer algebra.
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