Learn from Home Offer
Machine Learning Training (19 Courses, 29+ Projects)
This Machine Learning Certification includes 19 courses , 29 Projects with 178+ hours of video tutorials and Lifetime access.
You will also get verifiable certificates (unique certification number and your unique URL) when you complete each of them.It will explain you concepts such as Machine learning using Python, Deep learning, Data Science with R, Face Detection in Python, Bayesian Machine Learning, Projects on Machine learning and much more right from the basics to advanced concepts.
BESTSELLER
1
Machine Learning - Statistics Essentials
2
Machine Learning with Tensorflow
3
Hands-on Deep Learning Training
4
Machine Learning with R
5
Machine Learning with SciKit-Learn in Python
Offer ends in:
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* One Time Payment & Get Lifetime Access
* One Time Payment & Get Lifetime Access
What you get in this Machine Learning Training?
Online Classes
Technical Support
Mobile App Access
Case Studies
About Machine Learning Certification Course
| Course | No. of Hours | |
|---|---|---|
| Machine Learning with R 2022 | 3h 05m | |
| Machine Learning with Python 2022 | 5h 15m | |
| Project on Machine Learning - Covid19 Mask Detector | 2h 05m | |
| Machine Learning Project - Auto Image Captioning for Social Media | 2h 23m | |
| Mathematical and Statistics Foundations for Machine Learning | 8h 24m | |
| Machine Learning with Tensorflow | 13h 29m | |
| Hands-on Deep Learning Training | 10h 8m | |
| Machine Learning with R | 20h 28m | |
| Machine Learning with SciKit-Learn in Python | 8h 37m | |
| Project on ML - Shipping and Time Estimation | 2h 29m | |
| Project on ML - Supply Chain Demand Trends Analysis | 1h 09m | |
| Project on ML - Predicting Prices using Regression | 2h 18m | |
| Project on ML - Fraud Detection in Credit Payments | 2h 1m | |
| Project on ML - Banking and Credit Frauds | 44m | |
| Project on ML - Churn Prediction Model using R Studio | 1h 22m | |
| Project on ML - Random Forest Algorithm | 1h 29m | |
| Machine Learning Python Case Study - Predictive Modeling | 8h 27m | |
| Octave Machine Learning Training - Beginners to Beyond | 3h 34m | |
| Octave Machine Learning Training - Intermediate to Advanced | 2h 42m | |
| AI Artificial Intelligence with Python | 6h 15m | |
| Machine Learning using Python | 3h 26m | |
| AWS Case Study - Machine Learning | 2h 31m | |
| Deep Learning Tutorials | 1h 34m | |
| Data Science with R | 6h 2m | |
| Natural Language Processing (NLP) Tutorials | 1h 5m | |
| Bayesian Machine Learning: A/B Testing | 57m | |
| BIP - Business Intelligence Publisher using Siebel | 2h 19m | |
| BI - Business Intelligence | 14h 24m | |
| Artificial Intelligence and Machine Learning Training Course | 12h 15m | |
| Python Case Study - Sentiment Analysis | 1h 06m | |
| Projects and Case Studies on Machine Learning | 4h 44m | |
| Machine Learning Python Case Study - Diabetes Prediction | 1h 03m | |
| Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression | 2h 07m | |
| Project on R - HR Attrition and Analytics | 2h 43m | |
| Logistic Regression using SAS Stat | 4h 28m | |
| Linear Regression in Python | 2h 31m | |
| Python Data Science Case Study - Predicting Survival of Titanic Passengers | 2h 6m | |
| Project on R - Card Purchase Prediction | 2h 28m | |
| Machine Learning Python Case Study - Develop Movie Recommendation Engine | 51m | |
| R Practical - Employee Attrition Prediction using Random Forest Technique and R | 2h 2m | |
| Project on Term Deposit Prediction using Logistic Regression CART Algorithm | 1h 38m | |
| Project - Credit Default using Logistic Regression | 3h 2m | |
| Project - House Price Prediction using Linear Regression | 3h 12m | |
| Poisson Regression with SAS Stat | 2h 26m | |
| Machine Learning Project using Caret in R | 1h 58m | |
| Time Series Analysis in Python - Sales Forecasting | 2h 12m | |
| Machine Learning Project - K-Means Clustering using R | 43m |
| Course Name | Online Machine Learning Course Bundle |
| Deal | You get access to all 19 courses, 29 Projects bundle. You do not need to purchase each course separately. |
| Hours | 178+ Video Hours |
| Core Coverage | Machine learning using Python, Deep learning, Data Science with R, Face Detection in Python, Bayesian Machine Learning, Business Intelligence, Artificial Intelligence, Projects on Machine learning. |
| Course Validity | Lifetime Access |
| Eligibility | Anyone who is serious about learning Machine Learning and wants to make a career in this Field |
| Pre-Requisites | Familiarity with at least one programming language is recommended |
| What do you get? | Certificate of Completion for each of the 19 courses, 29 Projects |
| Certification Type | Course Completion Certificates |
| Verifiable Certificates? | Yes, you get verifiable certificates for each course with a unique link. These link can be included in your Resume/Linkedin profile to showcase your enhanced Machine Learning Skills |
| Type of Training | Video Course – Self Paced Learning |
| Software Required | Open Source Software |
| System Requirement | 1 GB RAM or higher |
| Other Requirement | Speaker / Headphone |
Online Machine Learning Course Curriculum
In this section, we talk about all the courses that are offered under our Machine Learning Training along with their details.
Goals
This course from EduCBA has been carefully crafted in order to upgrade oneself in the genre of Data Analysis and Data Science. This training will go along way in making you the data scientist organizations are looking out for by means of making you understand deeper concepts of Machine Learning!
Objectives
In the world where we generate 2.5 quintillion bytes (1 quintillion bytes = 1018 bytes!) every day, it becomes important for people who can read and derive meaning from that data. This course helps you be that person who can derive meaning out of this huge data with organizations. During this course, we would take you through different concepts starting from a beginner level to advanced concepts. One can master the concepts taught during this course so that it runs in the blood of the programmer and gets easy going for him to apply them in real-life situations. These topics when taught will boost up the confidence and the projects along with the course will add to push that confidence beyond 100%.
Course Highlights
Our machine learning course from EduCBA is crafted with care to bring the best to you in the most concise yet not missing out on the most updated technologies in the industry. To list some highlights of this course here are a few:
- This course will start off with statistics essentials to cover the portion of Statistics required for the course. To make the statistics during the course a little lighter, this section is designed.
- As the next portion, we would cover Machine learning with TensorFlow. TensorFlow is an open-source library or framework that eases out the process of data acquiring, model training, prediction showcasing and has a framework for improving results in the future.
- Once we have completed Machine Learning with TensorFlow, we would take a deep dive into Deep Learning. Deep learning is a subset of Machine Learning where the networks are capable of learning from even unstructured data just like. The human brain does.
- Some major highlights in terms of topics to be covered in the course include Natural Language Processing, Bayesian A/B testing, Business Intelligence Publisher using Siebel, Learning data science in R, Beginner to advanced level octave tutorial any many such more.
- During this course, one would get exposure to the technical depth of Supervised and Unsupervised Learning. Supervised learning includes regression and classification approaches along with a rule-based heuristic approach. Unsupervised includes clustering methodologies and in-depth dive onto that.
- This course will also teach tips and tricks for performing Exploratory Data Analysis (EDA).
Project Highlights
This course will take you through a ride through all the components required for fulfilling the needs of an organization from a data scientist. This course has been so carefully articulated that a person with no experience can learn from a wide variety of topics and projects this course offers. Some highlights of projects in this course are:
- This course offers various projects under the umbrella of machine learning. Projects on Churn Prediction, Fraud Detection are some old but gold projects. There are hands-on projects on the Random Forest algorithm and Supply Chain Demand Trends Analysis as well.
- In regard to the project in R, we have a project on HR Attrition and Analytics and card purchase prediction.
- There are some projects which are widely accepted as projects which enhance the thinking level of a data scientist and the same are included in our course. These projects include Credit Default prediction using logistic regression which is widely used as a baseline for many NBFCs or banks, House price prediction which is extensively used in real estate business, Term deposit prediction again used extensively by banks.
- This course also touches some portions of Siebel and even there we don’t hesitate to provide a hands-on experience for the same.
- From an exploratory data analysis standpoint, we do have projects which include the usage of ggplot2, R and Linear Regression.
- In the case of SAS as well we do have an extensive project to get into the groove of using SAS in a production-level environment.
Certificate of Completion
What is Machine Learning?
Now that we understood the course offerings, one might still have question like what machine learning is at the first place. So, before we move ahead, we shall spend some time to learn about machine learning and then we shall talk about other details of this particular course.
Machine learning is a sub field of computer science where machines are trained to make decision with the help of data provided without any human interfere. For example, if we could teach a computer to tell if a person is laying about something, then the computer might be using machine learning as a software.
There are huge applications of machine learning such as Face recognition, image classification, stock market prediction, Emotion detection, self-driving cars etc. More details about all these are covered in the training course videos.
Machine learning uses knowledge from mathematics, statistics, computer science and programming to build and deploy algorithms that can do one of those tasks mentioned above.
Artificial intelligence is also a similar word to machine learning but has a wider scope than the later. In AI, the problems are generally of bigger and more complex nature such as teaching a machine to translate a language into another. However, these days the two words are frequently used as synonyms i.e. carry more or less same meaning.
Almost all modern computers, software, mobile and apps are using machine learning in one form or another. Amazon, Netflix, Facebook, Google and almost all other social media providers, online stores etc. are using machine learning in their applications, products and solutions.
Industry Growth Trend
The machine learning market is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.[Source - MarketsandMarkets]
Average Salary
Average Salary$141,029 per year
The average salary for a Machine Learning Engineer is $141,029 per year in the United States.
[Source - Indeed]
[Source - Indeed]
Which Skills you will learn in this Machine learning course?
This machine learning training provides three most important and highly in demand skill. These skills are the tangible benefits of this online training course:
- Understanding of Fundamental concepts: To be a successful data scientist, it is very important that one understands each and every concept well enough. Machine learning is not only about programming and hence one needs to understand a lot of theory as well. This training course covers all the fundamental concepts in a very detailed manner.
- R language: R is a very important programming language for data scientists. This machine learning training spends a lot of time teaching R and also provides many projects where students can apply their R skills to solve the problem and thus can become very good at it. Having a great command over R can be very beneficial while seeking a job.
- Python programming: Python is again a very popular data science programming language. People skilled in Python are huge in demand. Especially those people who know both R and Python are very well received by industries and this Machine learning course therefore teaches both of these.
Pre-requisites
- This machine learning certification course has some pre-requisite to ensure that the candidates who enroll for it are well prepared to understand the course material. The pre-requisite are not too long and is also possible that a student can take a bridge course if pre-requites are not met.
- Students should have enough familiarity of basic linear algebra, calculus, probability and statistic. These courses need not be at a very high level. If you remember what you learnt in high school or junior college or can revise it quickly, then that should be enough.
- Familiarity with at least one programming language is recommended. Anyone language such as C, C++, Java, PHP etc. are fine. This ensure that you understand the programming examples and assignment and does not spend too much time there. If you have not done coding before, you can take a bridge course before enrolling for this machine learning training. This will make your life very easy.
Target Audience
- The machine learning certification is targeted for a specific audience and may not suit everyone. Following type of students or working professional is most suitable to take this machine learning training.
- Already working analyst, business intelligence professional, a junior data scientist who wants to hone their skill further and switch to better jobs.
- Managers and business leaders who want to build, nurture and lead a team of data scientists. For such people, this Machine learning course provides enough examples and business use cases to start with.
- Students and fresh graduates who want to build a career as data scientists. For such candidates, this Machine learning training course provides enough contents to make sure they get the job they deserve.
FAQ’s- General Questions
Does this machine learning course all the relevant material for becoming a data scientist?
Yes. It teaches all of what is needed to crack a data science interview and execute data science tasks in your organization. It makes you do projects and assignment to make sure you are able to solve problems in real life.
Will I be able to qualify the interview for ML roles after taking this machine learning training?
Most of our past students got successfully placed in MNC’s and startups as well after taking this course and so shall be you. Those students who are focused and completes all assignments and projects usually do much better in interviews and job application.
Is this machine learning certification heavily math oriented?
Some familiarity with high school math is recommended. But it is not all about mathematics. Mathematics help you understand the concept better and make you see a lot of insights and thus we recommended that you revise your math skill if you are not very confident. But at the same time, one can ignore the math part and still understand the content.
How much programming do I need to know to understand this machine learning training?
Knowledge of programming is required as most of the exercises are coding based. For non-technical background people or managers, the focus could be on application and concepts if they are not planning to do coding in their job.
Sample Preview of this Machine Learning Course
Career Benefits
- This course is very practical in nature. It does not only cover theoretical concepts but also hands-on exercises and projects. Thus, students find it easier to crack job interviews and solve real-life machine learning and data science problems. This is the most differentiating benefit of this course.
Many of our past students have managed to switch to great jobs are reputed companies after successfully going through this Machine learningcourse. - Salary increases is another great factor from this Machine learningcourse. On an average our candidates received from 30%- 55% hike in their salary post this course.
- Course reviews are great way to understand the impact of this machine learning course to our community. When we started we were really small with only a handful of candidates but now we are several hundred strong. This is a telling story of our success.
Machine Learning Course Testimonials
Machine Learning – Statistics Essentials
I really enjoyed this Machine learning course, and found the statistical approaches useful – especially the regression and cluster sampling sections. The course pacing was easy to understand, and the topics covered in a comprehensive but not over-explained way. Thanks for giving such an interesting and useful course!
Linked
Matthew Rolley
Great!
Nice introductory Machine learning certification course if you want to get a basic understanding of what Machine Learning is. You don’t need ridiculous technical chops to gain something from this Machine learning training course, it’s put together in a way that anyone can value from and truly understand it. I’d definitely recommend it to anyone who just wants to dip their toes in the Machine Learning waters.
Linked
Ammar Khan
Machine Learning with R
The Machine learning certification covers a wide range of areas into linear and multiple linear regression and decision tress. It also covers both theory and application using R neural network , time series analysis and gradient boosting machines. I have enjoyed learning in this Machine learning course very much and found it useful in my work.
Linked
Tsui Man Kit
Summary
This Machine learning training course is good and it shows practical examples as well. However in the first part it shows examples with not appropriate enlarge, so the commands and the outputs are not properly visible. I suggest to include more practical examples related to MatLab. The second part’s examples are clearly visible.
Linked
Attila Nagy
