Certificate Course in
Machine Learning using Python and R Training
- Get Trained by Trainers from ISB, IIT & IIM
- 24 Hours of Intensive Classroom & Online Sessions
- 60+ Hours of Practical Assignments
- 2 Capstone Live Projects
- 100% Job Placement Assurance
Academic Partners & International Accreditations
"As one of the hottest aspects of computer science, the Machine Learning market is projected to grow from $7.3 billion in 2020 to $30.8 billion in 2024." - (Source). Look around and you will see we are amidst the perfect storm for the growth in the field of Machine Learning, a subset of Artificial Intelligence. Machine learning & Artificial Intelligence are going to change the way we interact with everything in our environment. Both technologies when coupled together aid in processing operations with the utmost accuracy. Industries around the world, have realized the prospects of Machine Learning and are adopting it as a core technology. With new advancements in this field, Machine Learning is extensively implemented to make predictions and get valuable insight into business decisions and operations. So, grab hold of your business class ticket and soar into the most exciting careers in data analysis with the Machine learning course in India.
- Computer Skills
- Basic Mathematical Knowledge
- Basic Data Science Concepts
Machine Learning Course Overview
Discover the depths of machine learning using Python and R with the help of our Machine Learning with Python and R program. Build ML algorithms and statistical tools with the two most popular programming languages in the world. Use Python and R to enable regression analysis and build predictive models. Orient yourself with algorithm development on Black Box Techniques like Neural Networks and Support Vector Machine. This course equips the student with a strong foundation in Python, R, and RStudio. Specifically, the use of R studio to develop statistical software is highlighted. The student then develops algorithms for skewness and kurtosis, box plot, hypothesis testing (parametric and non-parametric test), correlation analysis, linear regression, multiple linear regression, logistic regression, multiple logistic regression, supervised machine learning, KNN, Naive Bayes, Decision Tree, Random Forest, ANN, and SVM. Enabling Unsupervised learning and Reinforcement Learning with Python and R is also dealt with. Students are trained to develop compelling data visualizations using Python and R. This is the most comprehensive course on Machine Learning with Python and R.
What is Machine Learning?
Every time we create new technology, we create a bigger buzz. Two major technologies sweeping the market are Artificial intelligence (AI) and Machine learning (ML). Machine Learning is a subset of Artificial Intelligence that focuses on designing systems that enable a machine to perform tasks without explicit coding. All the Artificial Intelligence advancements we hear about and the applications we see are all a result of Machine Learning Algorithms. Machine-learning Algorithms use a huge amount of data and statistics to find patterns and inferences it collects from the statistical models and complex algorithms.
What is R?
R is primarily a statistical software developing tool specifically tailored for statistical computing as well as graphical processing of data. It is an interpreter-based language and is very popular across multiple industries. R is used for data analysis, statistical modeling, time series forecasting clustering, etc. CRAN (Comprehensive R Archive Network) repository is R’s biggest strength with 7700+ packages that are specialized for all sorts of data analytical needs.
What is Python?
Python has emerged as a high-level programming language suitable for a variety of tasks in machine learning. With its simple, easy to understand syntax clubbed with its edit-test-debug cycle makes it a popular choice among programmers. Python is used for developing software, management of infrastructure, and data analysis. The biggest asset of the language is its collection of libraries and frameworks that can be utilized for Machine Learning, Automation, Web development, etc.
Machine Learning Training Learning Outcomes
We live in a world where humans and machines interact with each other every day to make our lives more comfortable. This has led to an exponential growth in the adoption of ML technologies. In the days to come, Machine learning & Artificial Intelligence are going to change the way we interact with everything in our environment. Both technologies when coupled together aid in processing operations with the utmost accuracy. Industries around the world, have realized the prospects of Machine Learning and are adopting it as a core technology. This machine learning course in India will allow you to work around various Machine Learning algorithms and build ML models. There is an escalating need for smart and accurate decision-making across industries and Machine learning is redefining the way we work today. In this course, the students will be exposed to the landscape of Machine Learning and its archetype of supervised and unsupervised learning. Students will also understand the popular machine learning approaches and the underlying mathematical relationships between the various algorithms..Gain expertise in this cutting-edge technology and work on real-life projects with this Machine Learning course that will help you to explore the process of investigating data to solve predictive tasks, such as speech recognition, object recognition, automatic algorithm configuration, time series forecasting, machine translation, and much more.
Block Your Time
Who Should Sign Up?
- Candidates aspiring to be Data Scientist, Machine Learning Expert, Analytics Manager / Professional, Business Analyst, Data Analyst, etc.
- Employees of organizations which are planning to devise proactive strategies using Machine Learning approaches
- Managers with knowledge of basic programming and decision makers who want to make data-driven decisions
Certified Machine Learning Course Modules
In today's world of Big Data where various technologies and digital platforms have only accelerated the generation of data, the question many are fighting to answer is how relevant is all this data. The emergence of Machine Learning has solved the puzzle of larger than life ‘Data’. Machine Learning is making quite an impact and has managed to grab the attention of many companies, because of its powerful computational processing abilities, continuously filtering the growing volumes of huge data sets, and offering affordable data storage options. This way it saves time and allows organizations to use the relevant data for better efficiency. The objective of this module is to provide a holistic view of Machine Learning, how it works, what it can and cannot do. The module will first introduce you to the installation of Python and R followed by connecting to a variety of data sources using Python and R. Each step of the way we will cover various topics of Machine learning with theory, application, and then dive deep into the inner workings of Machine Learning algorithms. Students will also learn Basic statistics, data visualization, and data manipulation using Python and R. You will also gain insight about Linear and Logistic regression and Decision tree using Python and R.
Learn two of the most powerful programming languages used in Data Analytics. Both R and Python are the top two tools used by Data Analytics professionals world over. Start learning from the very basics, right from installation and work your way up through simple commands, writing small functions and programs.
Both R and Python can connect to a wide variety of data sources. Under this module, learn how to establish a gateway between different databases with R and Python. Also, learn how to connect to external sources of data.
One of the major modules of Data Science is Machine Learning. Learn about the various modules that make up Machine Learning using the two most popular tools R and Python. Get introduced to the broad overview of ML and the various quality metrics with the help of R and Python.
In the real world, oftentimes, the datasets cannot be used as such and some amount of preprocessing activity needs to be done. Imbalance in the output classes is one of the common problems where sometimes the proportion may be as lopsided as 95% to 5% or even higher. Learn about the various methods and algorithms to address this problem of imbalanced data sets.
One of the integral parts of learning Data Science and working on Analytics projects is the sound understanding of Statistical tools. In this module learn about the need to know statistical measures and their application in Data Science. Also, learn how to visualize the data in a concise form to derive various meaningful insights.
The essence of analytics is to be able to get the story from the data. And for the data to be able to truly be useful one needs to munge the raw data to make it legible. Using tools like R and Python, learn how to manipulate data from the raw form to make it ready for subsequent ML algorithms. The topic is all the more important in the current context given that a lot of data is moving to the unstructured format.
Both R and Python while being classified under the object-oriented programming languages category, still require some traditional approach to programming whereby the user-defined function needs to be spelled out and the use of conventional program snippets is of utmost importance. In this module, learn how to create simple to complex user-defined functions and hone your programming skills in the context of machine learning.
As a data scientist one will be engaged in a multitude of data mining techniques in both supervised and unsupervised learning. One of the major variants of the same is reinforcement learning that enables machines to learn through rewards. Under this module, get introduced to all the supervised techniques of prediction and classification; learn about the major unsupervised learning methods and the application of reinforcement learning in Data Mining.
Under supervised learning one of the most popular methods of predicting numeric data is linear regression and for classifying categorical data is logistic regression. These two methods will be covered in detail under this module. And the participant will be introduced to multiple examples using R and Python.
Under the classification modeling, decision trees method has a special place even though they are not truly classification modeling techniques but rule-based algorithms. The popularity of Decision trees is in its simplicity, high accuracy, and most important the ability to explain behind- the- scenes working of the algorithm. Under this module, the participant will be introduced to working with Decision trees using R and Python.
Machine Learning Trends in India
In today's world of Big Data where various technologies and digital platforms have only accelerated the generation of data, the question many are fighting to answer is how relevant is all this data. The emergence of Machine Learning has solved the puzzle of larger than life ‘Data’. Machine Learning has become the heart of several social media platforms and is everywhere in this digital era helping you filter your spam messages and unwanted emails, helping you organize and classify your photos, helping you go shopping based on your product preferences, booking a hotel, the list is endless. Machine Learning has become an essential part of making predictions, getting valuable insight into business operations and providing solutions to the problem of the information era.
Machine Learning has become an essential part of the solution to the problem of the information era. According to the current trend it is estimated that between 80 percent to 90 percent of all basic customer-service requests will be handled by AI. Surpassing the movie, coffee, and LED lighting industry, Machine Learning is expected to become a $120,000,000 industry by 2025. This powerful technology has walked into our everyday lives and has empowered us in meaningful ways and has created more job opportunities that are set for rapid growth. A career as a Machine Learning engineer offers many career opportunities and it is reported that Artificial Intelligence and Machine Learning Fields are expected to create 2 million job opportunities by 2020. So, avail world-class training in India and step into the world of opportunities with the course on Machine Learning.
How we prepare you
Additional assignments of over 60+ hours
Live Free Webinars
Resume and LinkedIn Review Sessions
Lifetime LMS Access
Job Placements in Machine Learning fields
Unlimited Mock Interview and Quiz Session
Hands-on experience in a live project
Offline Hiring Events
Call us Today!
Machine Learning Course Panel of Coaches
Bharani Kumar Depuru
- Areas of expertise: Data Analytics, Digital Transformation, Industrial Revolution 4.0.
- Over 14+ years of professional experience.
- Trained over 2,500 professionals from eight countries.
- Corporate clients include Hewlett Packard Enterprise, Computer Science Corporation, Akamai, IBS Software, Litmus7, Personiv, Ebreeze, Alshaya, Synchrony Financials, Deloitte.
- Professional certifications - PMP, PMI-ACP, PMI-RMP from Project Management Institute, Lean Six Sigma Master Black Belt, Tableau Certified Associate, Certified Scrum Practitioner, AgilePM (DSDM Atern).
- Alumnus of Indian Institute of Technology, Hyderabad and Indian School of Business.
Sharat Chandra Kumar
- Areas of expertise: Data Science, Machine Learning, Business Intelligence and Data Visualisation.
- Trained over 1,500 professional across 12 countries.
- Worked as a Data Scientist for 14+ years across several industry domains.
- Professional certifications: Lean Six Sigma Green and Black Belt, Information Technology, Infrastructure Library.
- Experienced in Big Data Hadoop, Spark, NoSQL, NewSQL, MongoDB, R, RStudio, Python, Tableau, Cognos.
- Corporate clients include DuPont, All-Scripts, Girnarsoft (College-dekho, Car-dekho) and many more.
- Areas of expertise: Data Science, Machine Learning, Business Intelligence and Data Visualisation.
- Over 20+ years of industry experience in Data Science and Business Intelligence.
- Trained professionals from Fortune 500 companies and students from prestigious colleges.
- Experienced in Cognos, Tableau, Big Data, NoSQL, NewSQL.
- Corporate clients include Time Inc., Hewlett Packard Enterprise, Dell, Metric Fox (Champions Group), TCS and many more.
Get validation of your advanced skills and knowledge with the Machine Learning using Python & R. Join the growing community of developers and data scientists trained on Python & R.
FAQs on Machine Learning Course Training
You must have a very strong background in mathematics, particularly in linear algebra and calculus. You must also be proficient in probability and calculus. Programming knowledge in Python /R/C++ and Java is a must. It is good to have knowledge of distributed computing and advanced signal processing techniques.
Students must possess a Bachelors's degree in Mathematics/ Statistics/ Computer Science/ Data Science or a Bachelors's degree in Engineering ( any discipline). Students pursuing MCA can also apply for this course.
Once the assignments have been submitted the student receives a Course Completion Certificate. After this he can enroll for internship with INNODATATICS. Here he will work on a live project for 60 hours. Once he completes his internship , he will receive an internship certificate.
The learning outcomes of this course are
- Gain proficiency in analysing data and performing Data Wrangling, Data Cleansing, Data Manipulation
- Develop Machine Learning Algorithms including Black Box techniques like Neural Networks and Support Vector Machine
- Write algorithms in Python and R to facilitate Regression Analysis and other statistical measures
- Use Amazon Machine Learning Services for predictive modelling
- Create compelling Data Visualization for better reports
The modules in the course include:
- Connecting to Data sources
- Machine Learning
- Data Visualization
- Data Manipulation
- Functions and Programming
- Logistic regression
- Linear regression
- Data Mining Unsupervised
- Data Mining Supervised
- Reinforcement Learning
- Decision Trees
360DigiTMG offers one of the best Machine Learning courses in India. This course gives the student live project exposure in INNODATATICS.
The student must possess basic knowledge of mathematics and statistics. In addition, he must possess fundamental knowledge of computer science and data science.
This course has a duration of three months of which 24 hours are devoted to classroom sessions, 60 hours to assignments and e-learning and 60 hours on a live project.
On completing all the assignments and attending all classroom sessions you will receive a course completion certificate.
We assign a mentor for each student at the commencement of the course. If the student requires additional help we provide extra mentors.
The student will be trained on Python, R and R Studio in this course.
We provide 100% placement assistance. We assist the student in resume preparation and conduct mock interviews. We float the resumes to placement consultants with whom we have long standing association with. Once the student is placed we offer technical help for the first project on the job.
For beginners the salary would range between Rs.4 lakhs to Rs.5 lakhs.
With three plus years of experience a machine learning engineer can earn Rs 7.5 - 12 lakhs per annum.A Machine Learning Data Associate will earn between Rs.2.3 - 3.54 lakhs per annum.
We record all our classroom sessions and upload the videos in our Learning Management System AISPRY. If you miss a class you can source the video from AISPRY.
We have uploaded several free webinars on youtube on machine learning. These can be accessed from the link given below
Jobs in the field of Machine Learning in India
With training in Machine learning from India you will be able to work as a Machine Learning Engineer, Data Scientist, NLP Scientist, Business Intelligence Developer, Human-Centered Machine Learning Designer, the list is endless.
Salaries in India for Machine Learning
A Machine Learning Engineer in India gets an average salary of Rs.692,000, while someone with 2-4 years of experience gets Rs.790,597. An expert ML Engineer with 12-20 years of experience earns a whopping average compensation of Rs.1,817,135.
Machine Learning Projects in India
It’s always a plus to have hands-on experience in any technology you are working on. There are many projects one can work on using Machine Learning like Loan Prediction, Stock price prediction, Wine quality tests, Uber data analysis, Credit card fraud detection, etc.
Role of Open Source Tools in Machine Learning
The various tools in machine Learning help you work efficiently with data to derive valuable insights, discover new methods to train your model, and create new algorithms. In this course, we will use the various tools offered in Python and R for Machine Learning.
Modes of Training for Machine Learning
The course in India is designed to suit the needs of students as well as working professionals. We at 360DigiTMG give our students the option of both classroom and online learning. We also support e-learning as part of our curriculum.
Industry Application of Machine Learning
Today we use Machine Learning applications across various domains and the interesting features of Machine Learning have become the heart of many platforms. In the healthcare sector, we use it for drug discovery, in finance for fraud detection, in travel for pricing, in social media for implementation of various applications.