Machine Learning Classroom Training Bangalore | Machine Learning Course Bangalore

Best Machine Learning Training in Bangalore

“Become a Certified Machine Learning Professional”

Discover the full potential of Machine Learning with our comprehensive training program in Bangalore. Led by experienced industry professionals, our course is designed to give you the skills & knowledge you need to excel in the field. Join now and take your career to the next level with the best Machine Learning training in Bangalore.

Course Description

Machine Learning Course Bangalore | Machine Learning Training Bangalore | Machine Learning Institute | Machine Learning: It is the basic part of artificial intelligence which helps to attempt in data analyzing, by getting certified from leading and top machine learning institute, candidates become expert in delivering desired results in the career endeavors. NearLearn is one of the best machine learning course providers with high-quality standards and real-time projects which makes candidates professional and achieve confidence in getting their dream job.

  • Our Machine Learning Courses are well crafted and designed for candidates for all backgrounds and experiences.
  • Our all trainers are coming from industries and they hold a lot of experience in the technical domains.
  • We are very much focused on practical training that converts you to perform your own.
  • We have designed tasks in such a manner that it will create interest in your classroom study.
  • Machine Learning Programmed Completion from Industry trusted Certificate. Boost your Profession with the Certificate!
  • Bangalore is one of the Information Technology hubs for many software developers, where many startups and large enterprises are established with the latest technologies. Getting certification in top-rated Machine learning training in Bangalore will boost your career into the next level.

    NearLearn is located in Bangalore and has trained thousands of students and holding years of experience in professionally providing training.Our industry experts teach and train you cutting edge machine learning techniques with python from fundamental to advance level.

    We Provide Best Machine Learning Training in Bangalore, as per the modern industry standards. Our coaching plans will allow professionals to achieve placements. We are one of the Top Machine Learning Training Institute in Bangalore that contributes hands-on practical experience / practical attempt on live projects and will guarantee the job with the guidance of advance level Machine Learning Courses. At NearLearn Machine Learning Training in Bangalore is wielded by expert serving certified experts having 10+ years of expertise in performing real-time Machine Learning designs.

    The Machine Learning training in Bangalore will make the candidate professional, for this role requires the perfect amalgam of experience, data science knowledge, and using the correct tools and technologies. It is a good career choice for both new and experienced professionals. Aspiring professionals of any educational background with an analytical frame of mind are most suited to pursue this Program a basic understanding of 10+2 level mathematics and programming will be an added advantage, including:

  • Any Fresher or Jobseeker who has 10+2 level mathematics and basic programming knowledge.
  • Students in UG/ PG Programs with 10+2 level mathematics and basic programming knowledge
  • Computer skills, Basic knowledge of Mathematics and Basic knowledge of Data Science concepts.

    Contact us today and Get Machine Learning Certification in Bangalore.

    Reach us at +91-9739305140, If you are looking for Best Machine Learning Course Training in Bangalore

    Sample Certificate

    Course Curriculum

    Lecture1.1 Data science & its importancePreview

    Lecture1.2 Key Elements of Data Science

    Lecture1.3 Data Warehousing

    Lecture1.4 Business Intelligence

    Lecture1.5 Data Visualization

    Lecture1.6 Data Mining

    Lecture1.7 Machine Learning

    Lecture1.8 Artificial Intelligence

    Lecture1.9 Cloud Computing

    Lecture1.10 Big Data

    Lecture1.11 Artificial Intelligence: A previewPreview

    Lecture1.12 What is Artificial Intelligence & its importance

    Lecture1.13 Artificial Intelligence vs Machine Learning

    Lecture2.1 What is Machine Learning (ML)?Preview

    Lecture2.2 How machines learn Preview

    Lecture2.3 Types of learning: Supervised, Semi-supervised, Unsupervised, Reinforcement

    Lecture2.4 Basics of Classification, Regression and Clustering algorithms

    Lecture2.5 Creating your first Prediction Model

    Lecture2.6 Training & Model evaluation

    Lecture2.7 Choosing Machine Learning algorithm

    Lecture3.1 A quick refresh on basic intermediate maths

    Lecture3.2 Linear Algebra (Vectors, Matrix, Eigen Values)

    Lecture3.3 Probability and Statistics

    Lecture3.4 Hypothesis testing

    Lecture3.5 Optimization

    Lecture4.1 A quick crash course on basics of PythonPreview

    Lecture4.2 Python Object and Data Structure

    Lecture4.3 Python Comparison Operators

    Lecture4.4 Python Statements

    Lecture4.5 Methods and Functions

    Lecture4.6 Milestone Project – 1

    Lecture4.7 Object-Oriented Programming

    Lecture4.8 Modules and Packages

    Lecture4.9 Errors and Exception Handling

    Lecture4.10 Milestone Project – 2

    Lecture4.11 Built-in Functions

    Lecture4.12 Python Decorators

    Lecture4.13 Python Generators

    Lecture4.14 Final Capstone Python Project

    Lecture4.15 Advanced Python Modules

    Lecture4.16 Advanced Python Objects and Data Structures

    Lecture4.17 Advanced OOP

    Lecture4.18 Parallel Processing

    Lecture4.19 Python Packages [Statsmodels, Sci-kit Learn, Scipy, Numpy, Pandas, Matplotlib, Seaborn, etc.]

    Lecture5.1 Data Collection & Preparation

    Lecture5.2 Data Mugging

    Lecture5.3 Outlier Analysis

    Lecture5.4 Missing value treatment

    Lecture5.5 Feature Engineering

    Lecture5.6 Data TransformationPreview

    Lecture5.7 Normalization vs Standardization

    Lecture5.8 Creating Dummies

    Lecture5.9 Dimensionality Reduction

    Lecture5.10 Principal Component AnalysisPreview

    Lecture6.1 Supervised Machine Learning algorithms

    Lecture6.2 Linear RegressionPreview

    Lecture6.3 Logistic RegressionPreview

    Lecture6.4 Decision/Classification

    Lecture6.5 Tree Ensemble Models

    Lecture6.6 Bagging

    Lecture6.7 Boosting

    Lecture6.8 Random Forest

    Lecture6.9 K-Nearest Neighbours (KNN)

    Lecture6.10 Naive Bayes

    Lecture6.11 Neural Network (Deep Learning)

    Lecture6.12 Support Vector Machine

    Lecture6.13 Unsupervised Machine Learning algorithms

    Lecture6.14 Clustering with K-means Clustering

    Lecture6.15 Bias-Variance Trade off

    Lecture6.16 Regularization

    Lecture6.17 Parameter tuning & grid search optimization

    Lecture7.1 Real life cases with Python

    Lecture8.1 Students would be given challenging real life cases to solve – just to augment their learning skills.

    Register Machine Learning Course in BTM
    35, 000 + GST
    30, 000 + GST

    (0% Interest on EMI)


    Machine Learning Course

    Upcoming Machine Learning Trainings

    October 02nd | Weekday | 8 Weeks | 09:30AM TO 10:30AM

    October 07th | Weekend | 12 Weeks | 10AM TO 12PM

    October 03rd | Weekday | 8 Weeks | 09:30AM TO 10:30AM

    October 08th | Weekend | 12 Weeks | 05PM TO 07PM

    October 05th | Weekday | 8 Weeks | 09:30AM TO 10:30AM

    October 14th | Weekend | 12 Weeks | 10AM TO 12PM

    October 16th | Weekday | 8 Weeks | 09:30AM TO 10:30AM

    October 21st | Weekend | 12 Weeks | 05PM TO 07PM

    October 18th | Weekday | 12 Weeks | 09:30AM TO 10:30AM

    October 28th | Weekend | 8 Weeks | 10AM TO 12PM

    View All Upcoming Trainings


    Training Features

    Instructor-led Live Sessions
    We offer interactive and instructor-led live sessions on machine learning training. This allows our students to ask questions and receive real-time feedback from experienced professionals.

    Real Time Case Studies
    We provide real-life case studies so that you can practice your skills and learn how to apply them practically. Our instructors will help you identify case studies relevant to your specific industry or field of study so that you can become a more well-rounded professional.

    Assignments
    Our course includes various assignments that will test your understanding and give you hands-on experience. Each assignment focuses on different aspects of machine learning so that you will have an in-depth knowledge of the subject by the end of the course.

    Live Projects
    We also assign projects for our students. These projects tackle challenges organizations face in various industries using machine learning tools and techniques. Working on such projects exposes you to complex problems and helps hone your problem-solving skills.

    Training Certification
    After completing our machine learning course, you will be awarded a certification that is widely recognized in the market. This certificate signifies that you have acquired specialized knowledge and understand the principles behind this technology.

    100% placement
    We strive to ensure that our students get placed in their dream jobs after completing our program. We partner with leading companies to connect our alumni with the right opportunities and guide them throughout their job search.

    Trainer Profile


    Brief Info

    A Tech Enthusiast with expertise in Artificial Intelligence, Machine Learning, Internet of Things, Deep Learning and grip on R and Python.

    Deepak is a Mathematics and Computing graduate from IIT-BHU, Varanasi in 2010. He has an industry experience of 8+ years with specialization in web technologies, cloud infrastructure development and databases. He always is on a lookout for latest technologies and how their use can help us solve real world problems. Recent advancements in field of Internet of Things and Machine Learning have caught his eye. He likes the field and is actively involved in learning, developing and letting others know about the immense potentials of it.

    Deepak

    Data Science consultant

    Educational Qualification

    Graduation: Indian Institute of Technology, BHU, Varanasi Professional

    Experience

    1. Worked as Senior Software developer at Oracle India for 5 year on Web Development and Cloud Infrastructure Team
    2. Currently works as a freelance developer and trainer with NearLearn on IoT, Machine Learning & Artificial Intelligence since 4 years.
    3. Trained Corporate on various technologies like IoT, Machine Learning, Python, Artificial Intelligence

    Training Experience

    Trained more than 10000+ professionals, students and Faculty till now Delivered trainings to corporates on technologies like IoT and Machine Learning.
    Some of our esteemed clients where training has been conducted are Accenture, JP Morgan,UTC, UST Global Compucom, Kronos HARMAN, BNP Paribas Epsilon, SIT Tumkur LPU, Jalandhar NIET, Noida FDP, NITTE Meenakshi, Bangalore BR Ambedkar Institute of Technology, Bangalore ,FDP, Christ University Bangalore FDP, Reva University Technology Expertise

    1. Machine Learning with Python
    2. IoT
    3. Python
    4. Artificial Intelligence
    5. C/C++, Data Structure, Algorithms
    6. Django – Python Framework
    7. C/C++
    8. Java
    9. J2EE
    10. Networking
    11. Cloud Computing
    12. Web Dev.: HTML/Javascript/CSS



    General Questions

    Machine Learning is a part of artificial intelligence that develops the ability of machines or devices to perform automatically without explicit programs. This has the ability to improve from previous data and learn from experience. The machine learning mainly focused on computer programs that can access data and apply it to learn on own.

    Applying Machine Learning in business operation saves time and money that it has the potential to control the automation of process and impacts on the future of the companies. The latest technology such as machine learning involves in the customer care industry, as it allows peoples to get things done more rapidly and effectively. It has features like virtual assistants, natural language processing to operate the automation that responds to every query of customers and increases retention.

    The automation technology such as machine learning helps the business to personalize their interaction or conversions with customers and improves sales and produces insights for better productivity. With the help of a machine, learning companies can earn a better income and can save time with data-driven decisions. The core algorithms can help to eliminate dangers and deception, secure totally protected methods and improve customer compensation.

    3 Vs concept of data can be defined with dimensions of volume, variety, and velocity. Volume represents the quantity of data collected; variety defines the number of types of data stored and velocity points to the acceleration of data processing.

    The 3+ Vs of Big Data are best signs of when data is big and require beginning to tackle data shortages with newer, and it creates more scalable methods.

    Machine Learning has a huge impact on the entertainment industry, in August 2016 IBM announced the release of the trailer for 20th century Fox horror movie produced by morgan by applying machine learning on it. The research engineers trained the system with 100 horror movies classifying stories from every of the movie scenes into what the team called "moments," and then explaining them based on parts of visual, audio and scene formation.

    Once the program was familiar of the types of scenes contained in a typical suspense/horror movie trailer, the full-length film was given and the Morgan trailer was recommended for 10 moments. A maximum of six minutes of footage from the 90-minute film was taken, resulting in a 24-hour cycle from beginning to end.

    While the impact of integrating AI and Machine Learning have resulted in cost savings in trailer production, the estimated $8 million budget film in global box office sales grew just over $7.3 million. However, as Morgan is the first attempt to use AI for trailer development, the direct impact on ticket sales is too soon to be accurately determined.

    Most of the businesses nowadays apply descriptive analytics, as it is the most basic form of analysis. It is one of the forms of business intelligence and data analysis, explores to present a depiction of experiences and terms in an understandable form, to each informs or develops data for a future report.

    The main approach to understanding data and existing patterns is descriptive analysis. In the Descriptive Analysis, data structure, existing rules or patterns, and so on can be used to illustrate. Descriptive analysis can be four main groups of categories.

  • Operational reports
  • Statistical analysis
  • Data mining methods
  • Diagnostic analytics allows companies to dig deeper to see evolving behaviors and obtain more intelligent reports understanding of a specific issue. A healthcare facility, for example, contrasts the response of patients to an advertising campaign in different parts of the country; a retailer scrutinizes sales down to subcategories.

    Enabled by machine learning, diagnostic analysis helps to prevent implicit bias and misunderstanding of possible causes. Devices perform well at identifying patterns, finding variations, mapping "atypical" occurrences, and recognizing main factors beyond key performance indicators (KPIs).

    The predictive analytics defines what is likely to occur. This uses discoveries in descriptive and predictive analytics to identify patterns and make predictions developments. The focus of predictive analysis is the use of statistics for predictive forecasting or identification.

    Prescriptive analytics aims to recommend what steps should be taken to prevent a future problem or to understand the full potential of an emerging trend. This method of data analysis involves not only the compilation of authentic information but also the aggregation of external data based on the concept of statistical algorithms.

    Data Mining and Machine Learning are fields that have been driven by each other, but they have many things in common, yet they have different objectives.

    Data mining is performed out by humans for certain datasets to find interesting similarities between datasets. Data mining uses techniques developed by machine learning to predict the outcome; Whereas Machine Learning is the capability of a device to learn from past datasets.

    Statistical learning is a method for the analysis of statistics-based data that can be categorized as supervised or unsupervised. Supervised statistical learning includes the design of a predictive model for predicting or predicting performance based on one or more input and output; while in unsupervised statistical learning, there are inputs but no supervising output; but we can learn relationships and structure from such data.

    No, you don't need to know about machine learning before taking this course. However, a basic understanding of coding and mathematics is recommended to make the most of this training.

    Yes, we do provide placements post-completion of the course. We have partnered with some leading companies across industries that hire our graduates based on their skill level and experience. We also provide guidance and support in preparing resumes, attending interviews and getting through aptitude tests if needed.

    It typically takes 8-10 weeks to complete our courses, and once you finish the entire program, you'll receive your certificate within 7-10 business days. The certificate is valid worldwide and has immense value when looking for job opportunities in machine learning.

    Yes! All our courses come with lifetime access to our online portal that allows students to view videos, download notes and access material even after completing their training program. This will enable students to refer to the material whenever needed during their projects or research endeavours.

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