Machine Learning
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Machine Learning
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The study of computer algorithms that may develop automatically through use of data and experience is known as machine learning. It is a subfield of computer science and artificial intelligence (AI). With the aid of machine learning, practically every element of our everyday lives—housing, automobiles, shopping, ordering takeout, etc.—will become simpler and more effective.
OVERVIEW OF THE PROGRAM
Machine learning, or the study of algorithms, has significantly aided in the evolution and use of artificial intelligence over the past ten years. Regardless of the industry it is used in, it is a fully data-driven idea that analyses user behaviour and business operational patterns. With the help of our certification programmes, you will be able to comprehend the use and future of machine learning, get knowledge of how ML is applied in many sectors through our internship programmes, and master the python programming abilities required to succeed as an ML Engineer.
Live Training sessions
Distinguished Mentors
Internship Experience
Industry Relevant Projects
LMS Access
Professional Certifications
Skill Covered
- Data Wrangling & Exploration
- Machine Learning Algorithms
- Statistics
- Python Programming
- Natural Language Processing (NLP)
Key Features
- Interactive Sessions with Distinguished Mentors
- 200+ Hours of Online Sessions
- Flexible Payment Model
- Certifications From Internationally Renowned Universities
- Practical Exposure Through Industry-Relevant Projects and Internships
- Mock Test / Mock Interviews to Make you Interview Ready
- Career Counselling
- Resume Building Assistance
WHY LEARN FROM INTERNINFOTECH?
Our training curriculum includes ideas ranging from basic to advanced, allowing freshmen to excel in their careers.
- Course Introduction
- Programming Basics
- Decoding Artificial Intelligence
- Fundamentals of Machine Learning
- Types of machine learning
- Machine Learning Workflow
- Performance Metrics
- Supervised vs unsupervised learning
- Classification vs regression
- Introduction to machine learning algorithms
- Types of machine learning algorithms
- Machine learning techniques
- Machine learning approaches
- Overview of common algorithms:
- Linear Regression
- Logistic Regression
- Decision Tree
- SVM
- Naive Bayes
- kNN
- K-Means
- Random Forest
- Dimensionality Reduction Algorithms
- Gradient Boosting algorithms
- Training, Testing
- Cross validation Data Pickling
- Scaling Technique
- Error Metrics Features and label
- Performance Metrics
- Supervised vs unsupervised learning
- Classification vs regression
- Support vector machine
- K-means clustering
- Random forest linear
- Introduction to Joins
- Working with geodata & what-ifs parameters
- Creation, calculation, and grouping of fields
- Sorting, filtering, & analyzing data
- What is natural language?
- Natural Language Toolkits (NLTK)
- Stopwords
- Stemming
- Lemmatization
- What is sentiment analysis?
- Native and bayes
- Probability & distribution
- Central limit theorem
- Hypothesis testing
- Categorical data
- Introduction
- Types of productive modelling
- Data extraction
- Data exploration
- Data Visualization
- Building a data visualization library
- Numpy
- Pandas
- Course Introduction
- Programming Basics
- Decoding Artificial Intelligence
- Fundamentals of Machine Learning
- Types of machine learning
- Machine Learning Workflow
- Performance Metrics
- Supervised vs unsupervised learning
- Classification vs regression
- Introduction to machine learning algorithms
- Types of machine learning algorithms
- Machine learning techniques
- Machine learning approaches
- Overview of common algorithms:
- Linear Regression
- Logistic Regression
- Decision Tree
- SVM
- Naive Bayes
- kNN
- K-Means
- Random Forest
- Dimensionality Reduction Algorithms
- Gradient Boosting algorithms
- Training, Testing
- Cross validation Data Pickling
- Scaling Technique
- Error Metrics Features and label
- Performance Metrics
- Supervised vs unsupervised learning
- Classification vs regression
- Support vector machine
- K-means clustering
- Random forest linear
- Introduction to Joins
- Working with geodata & what-ifs parameters
- Creation, calculation, and grouping of fields
- Sorting, filtering, & analyzing data
- What is natural language?
- Natural Language Toolkits (NLTK)
- Stopwords
- Stemming
- Lemmatization
- What is sentiment analysis?
- Native and bayes
- Probability & distribution
- Central limit theorem
- Hypothesis testing
- Categorical data
- Introduction
- Types of productive modelling
- Data extraction
- Data exploration
- Data Visualization
- Building a data visualization library
- Numpy
- Pandas
PRICING PLAN
We provide best programs at affordable price and student friendly.
GOLD
₹ 25000
- Course Duration : 4 months
- Live classes : 60 Hours
- Video Content : 70 Hours
- 2 Major + 2 Minor Projects
- Program Completion Certificate
- Co-branded internship Certificate*
- 100% Job Assistance (T&C Applied)
- 100% Paid Internship* Post Complition of Program* ( T&C Applied)
PLATINUM
₹ 30000
- Course Duration : 6 months
- Live classes : 100 Hours
- 4+ Hrs of Live Sessions
- Video Content : 70 Hours
- 3 Major + 2 Minor Projects
- Program Completion Certificate
- Co-branded internship Certificate*
- 100% Job Assistance (T&C Applied)
- 100% Paid Internship* Post Complition of Program* ( T&C Applied)
What Our Clients Say
Our Alumni Work At
Our alumni are already starting to make waves in their
industries. Our former students are already working in high-
profile industries and are shaping our futures.
Frequently Asked Questions
What kind of certification will I get?
You will receive certifications from internationally known colleges that are pertinent to your field of study after completing your course.
Will I get placed after completing this course?
Yes. Our goal at InternsTech is to prepare our students for the workplace. You will not only have the necessary knowledge and skills, but you will also have had experience with our programme before the hiring process. Also, we will provide you with all the essential assistance, including help with resume development, career counselling, and interview preparation. To make sure you get the ideal job, our mentors collaborate closely with our placement staff.
How is the job guarantee program different from your other courses?
Our instruction is based on the same core ideas. The job guarantee programmes, on the other hand, are a more rigorous training schedule with the aim of getting our students fully prepared for the workforce. Also, this programme offers expert aid, counselling, and guidance in addition to help with resume development. At InternsTech, our staff will make sure that you begin in the career of your choice.
Will this program guarantee me a job?
Yes. Our goal at InternsTech is to prepare our students for the workplace. You will not only have the necessary knowledge and skills, but you will also have had experience with our programme before the hiring process. Also, we will provide you with all the essential assistance, including help with resume development, career counselling, and interview preparation. To ensure that you land the ideal position, our mentors collaborate closely with our placement staff.



















