- A warm welcome
- Linear algebra
- High dimensional vector spaces
- Supervised vs. unsupervised machine learning
- How ML pipelines work
- Introduction to sparkML
- What is systemML (1/2)?
- What is systemML (2/2)?
- How to use apache systemML in IBM watson studio
- Extract - transform - load
Advanced Machine Learning and Signal Processing
Study more about the Unsupervised Machine Learning Models by enrolling for the course on Advanced Machine Learning and ...Read more
Expert
Online
4 Weeks
Quick Facts
particular | details | |||
---|---|---|---|---|
Medium of instructions
English
|
Mode of learning
Self study
|
Mode of Delivery
Video and Text Based
|
Course overview
The online program on Advanced Machine Learning and Signal Processing by Coursera is a part of the series of programs that are offered in the domain of “advanced machine learning and signal processing”. The Advanced Machine Learning and Signal Processing training is part of the courses that are offered by IBM on advanced data science specialization. In the course, the frameworks for python using SparkML and Scikit-Learn will be introduced. The Advanced Machine Learning and Signal Processing certification syllabus will be covered on the digital platform within a time frame of 28 hours.
The highlights
- 28 hours total course duration
- Subtitles in English, Russian, Arabic, Portuguese (European), French, Vietnamese, Italian, German, Spanish
- Shareable certificate
- Program by Coursera
- Advanced level course
- Course offered by IBM
- Deadlines flexible
- 100% online program
Program offerings
- Subtitles
- Online course
- Video lectures
- Assignments
- Practice sets
- Self assessment quizzes
Course and certificate fees
- Advanced Machine Learning and Signal Processing fee for the enrollment is free for 7 days only.
Advanced Machine Learning and Signal Processing Fee Structure
Particulars | Fee Amount in INR |
Advanced Machine Learning and Signal Processing - Audit course | Free |
Advanced Machine Learning and Signal Processing - 1 month | Rs.4,018/- |
Advanced Machine Learning and Signal Processing - 3 months | Rs.8,037 /- |
Advanced Machine Learning and Signal Processing - 6 months | Rs.12,056 /- |
certificate availability
Yes
certificate providing authority
Coursera +1 more
Eligibility criteria
Certification Qualification Details
Candidates will qualify for the Advanced Machine Learning and Signal Processing certificate only after they complete the course in the stipulated time. The students will receive both a Coursera certificate and an IBM batch.
What you will learn
The students will learn about the following after they complete the Advanced Machine Learning and Signal Processing online course-
- The candidates will be studying the applications of signal decomposition.
- The chapters of wavelet transform will be covered in detail.
- Applicants will have their skills developed in the genre of SVM demo.
- In the Advanced Machine Learning and Signal Processing certification syllabus the students will cover the chapter of systemML.
- Candidates will further be studying the working mechanisms of logistic regression.
The syllabus
Week 1: Setting the stage
Videos
Readings
- Object Store
- IMPORTANT: How to submit your programming assignments
- Hands-on Lab: Sign Up for IBM Cloud Account
Practice Exercises
- Machine Learning
- ML Pipelines
Week 2: Supervised Machine Learning
Videos
- Linear Regression
- LinearRegression with Apache SparkML
- Linear Regression using Apache SystemML
- Batch Gradient Descent using Apache SystemML
- The importance of validation data to prevent overfitting
- Important evaluation measures
- Logistic Regression
- LogisticRegression with Apache SparkML
- Probabilities refresher
- Rules of probability and Bayes' theorem
- The Gaussian distribution
- Bayesian inference
- Bayesian inference - example
- Maximum a posteriori estimation
- Bayesian inference in Python
- Why is Naive Bayes "naive"
- Support Vector Machines
- Support Vector Machines using Apache SparkML
- Crossvalidation
- Hyper-parameter tuning using GridSearch
- Decision Trees
- Bootstrap Aggregation (Bagging) and RandomForest
- Boosting and Gradient Boosted Trees
- Gradient Boosted Trees with Apache SparkML
- Hyperparameter-Tuning using GridSeach and CrossValidation in Apache SparkML on Gradient Boosted Trees
- Regularization
Reading
- Classification evaluation measures
Practice Exercises
- Linear Regression
- Splitting and Overfitting
- Evaluation Measures
- Logistic Regression
- Naive Bayes
- Support Vector Machines
- Testing, X-Validation, GridSearch
- Enselble Learning
- Regularization
Week 3: Unsupervised Machine Learning
Videos
- Introduction to Unsupervised Machine Learning
- Introduction to Clustering: k-Means
- Hierarchical Clustering
- Density-based clustering (Guest Lecture Saeed Aghabozorgi)
- Using K-Means in Apache SparkML
- Curse of Dimensionality
- Dimensionality Reduction
- Principal Component Analysis
- Principal Component Analysis (demo)
- Covariance matrix and direction of greatest variance
- Eigenvectors and eigenvalues
- Projecting the data
- PCA in SystemML
Reading
- Reading on Clustering Evaluation and Assessment
Practice Exercises
- Clustering
- PCA
Week 4: Digital Signal Processing in Machine Learning
Videos
- Signal decomposition, time and frequency domains
- Fourier Transform in action
- Signal generation and phase shift
- The maths behind Fourier Transform
- Discrete Fourier Transform
- Fourier Transform in SystemML
- Fast Fourier Transform
- Nonstationary signals
- Scaleograms
- Continous Wavelet Transform
- Scaling and translation
- Wavelets and Machine Learning
- Wavelets transform and SVM demo
Practice Exercises
- Fourier Transform
- Wavelet Transform
Admission details
Filling the form
For getting selected for the course the students will have to visit the official site of the Advanced Machine Learning and Signal Processing online course.
Step 1: Candidates are requested to visit the official course URL.
Step 2: In the next step the students have to click the button titled “enrol” to begin the process of learning.
Step 3: But they have to create a registered account id to log in and access the course.
Step 4: After successfully signing up, candidates will be required to make the fee payment and enrol for the programme.
Step 5: After successfully paying the amount, they can start learning.
Scholarship Details
Financial aid is available but the amount has not been specified.
How it helps
The Advanced Machine Learning and Signal Processing certification benefit the students by providing them with a double certification from Coursera and IBM. The course is being offered and will be conducted by professionals from IBM. The Machine learning certificate that the students will be rewarded with can be shared by the students on various platforms for securing better job opportunities and career options. To make the course more approachable the registration fee for the course has been made free and also a free trial period for seven days has been offered. Later the candidates need to pay a nominal fee to continue further if they find it apt after the trial period ends.
Instructors
FAQs
By whom will the classes be conducted?
The classes in the Advanced Machine Learning and Signal Processing online course will be conducted by professionals from IBM.
What is the total duration of the course?
The course will be held for a total period of 28 hours on the digital platform.
What is the course level?
The Advanced Machine Learning and Signal Processing training is an advanced level program.
Are subtitles available in the session?
Yes, subtitles on multiple languages are available in the Advanced Machine Learning and Signal Processing course.
Where can the students apply for the course?
The students can apply for the Advanced Machine Learning and Signal Processing certification course from the main website of Coursera or from the program URL.
Articles
Popular Articles
Latest Articles
Similar Courses
Production Machine Learning Systems
Google via Coursera
Four Rare Machine Learning Skills All Data Scienti...
SAS Institute via Coursera
Machine Learning Devops Engineer
Udacity
End-to-End Machine Learning with TensorFlow on GCP
Google via Coursera
Quantum Machine Learning
University of Toronto, Toronto via Edx
Machine Learning Fundamentals
UC San Diego via Edx
Machine Learning
Columbia University, New York via Edx
Probabilistic Graphical Models 3 Learning
Stanford via Coursera
Courses of your Interest
TOGAF 9 Combined Level 1 and Level 2 Training
SkillUp Online via Simplilearn
Advanced Certificate Program in DevOps
CMU School of Computer Science, Pitts... via TalentSprint
Mastering Deep Learning Using Apache Spark
Simpliv Learning
Devops with AWS CodePipeline Jenkins and AWS CodeD...
Simpliv Learning
Machine Learning with Python from Linear Models to...
MIT Cambridge via Edx
Big Data Capstone Project
The University of Adelaide, Adelaide via Edx
Advanced Certification Program in Big Data
Belhaven University, Mississippi via Intellipaat
Computer Applications of Artificial Intelligence a...
Purdue University, West Lafayette via Edx
Advanced Power Searching With Google
Google via Edx
More Courses by IBM
Cloud Application Developer Capstone
IBM via Edx
Full Stack Application Development Capstone Projec...
IBM via Coursera
Advanced Data Science Capstone
IBM via Coursera
Artificial Intelligence Workflow Artificial Intell...
IBM via Coursera
AI Capstone Project with Deep Learning
IBM via Coursera
Applied AI with DeepLearning
IBM via Coursera
Applied Deep Learning Capstone Project
IBM via Edx