MCA in Machine Learning: Course, Admission, Syllabus, Colleges, Jobs, Salary

Machine learning has emerged as a rapidly growing field in recent years, fueled by the increasing demand for data-driven solutions across various industries. It is a subfield of artificial intelligence (AI) that involves developing algorithms and models that can learn from and make predictions on data. 

To pursue a career in machine learning you can opt for a higher degree like MCA Program. This can open up a world of opportunities in a highly competitive job market. In this field, you can work on developing cutting-edge solutions that can impact people's lives positively.  

In this article, we will discuss the different career paths available in machine learning and the skills required to excel in this field.

What is Machine Learning? 

Machine learning is a type of artificial intelligence that allows computer systems to learn and improve from experience, without being explicitly programmed. It is the process of training a computer to make predictions or decisions by feeding it large amounts of data and allowing it to learn patterns from that data. The computer can then use this learned knowledge to make accurate predictions or decisions on new data it hasn't seen before. In simple terms, machine learning is a way for computers to learn and improve from experience, just like humans do.

MCA Course Overview 

Course Level	Post Graduate
Course Duration	2 Years
Eligibility Criteria	Graduation with minimum 50% Marks and Mathematics as a compulsory subject.
Entrance Exam	TANCET, WB JECA, NIMCET, PGCET, IPU-CET, CUET-PG
Average Course Fee	₹ 1.5 Lakhs
Average Initial Salary	₹ 7.58 Lakh per annum

Admission Requirements for MCA in Machine Learning

To get admission into an MCA Program one can either take admission on a merit basis or through an entrance exam. Most reputed institutes take students via their entrance exam scores. These entrance examinations are TANCET, WB JECA, NIMCET, PGCET, IPU-CET, and CUET-PG. 

The general eligibility criteria followed for admission are-

• You should have a graduation degree from a recognised university, Graduation in BCA/B.E or B.Sc. in Computer Science is preferred with mathematics as a compulsory subject. 
• The minimum aggregate marks for admission may vary from university to university but generally, it is set to 50% of marks. 

Syllabus for MCA in Machine Learning and Artificial Intelligence

Here is the general syllabus for an MCA in Machine Learning and AI. 

Semester-I	Semester-II
Professional Communication	Research Methodology
Core Java	Data Structures and Algorithm Design
Advanced Database Management Systems	Cognitive Analysis and Social Skills for Professionals
Advanced Software Engineering Principles	Network Security and Cryptography
Graph Theory and Combinatorics

Semester-III	Semester-IV
Unix/ Linux Programming	Major Project
Seminar (Evaluation)
Cloud Infrastructure and Services
Quantitative Aptitude
Professional Ethics
Deep Learning
Reinforcement Learning

Top colleges offering MCA in Machine Learning

Name of the College	NIRF Ranking	Entry Criteria	Total Fees (approx)	Average Package
Amity University	22nd	Direct Admission	₹4.94 Lakh	₹4-4.5 LPA
Delhi University	23rd	CUET	₹47,290	₹9 LPA
SRM University	24th	Direct	₹2.25 Lakh	₹2.5 LPA
NMIMS Global Access School for Continuing Education.	25th	NMIMS	₹2.25 lakh	₹4.1 LPA
Chandigarh University	29th	CUET	₹2.80 Lakh	₹6 LPA
Lovely Professional University	47th	LPUNEST	₹4 Lakh	₹8-9 LPA
Guru Gobind Singh Indraprastha University	66th	IPU CET	₹2-4 Lakh	₹7 LPA
SAGE University	-	Direct	₹90,000	₹5 LPA
G.D Goenka University	-	Direct	₹2.20 Lakh	₹4.3 LPA
KR. Mangalam University, Gurgaon.	-	Direct	₹2 lakh	₹6 LPA

Jobs and career prospects in Machine Learning 

Machine learning has become a popular field in recent years due to the increasing demand for data-driven solutions across various industries. As a result, the job market for machine learning professionals has expanded significantly, and there are numerous career paths available in this field. Some of the most common jobs in machine learning include:

1. Machine learning engineer: This is a technical role that involves designing and implementing machine learning models, developing algorithms, and building data pipelines. A machine learning engineer needs to have expertise in programming languages like Python, data processing tools like SQL, and machine learning frameworks like TensorFlow and PyTorch.
2. Data scientist: This role involves analysing and interpreting complex data sets to extract insights and make data-driven decisions. A data scientist should have a strong background in statistics, programming, and machine learning algorithms.
3. Data analyst: This role involves collecting, cleaning, and analysing data to identify trends and patterns. A data analyst should be proficient in data visualisation tools, SQL, and basic programming languages like Python or R.
4. Research scientist: This role involves conducting research and developing new algorithms and models to solve complex machine-learning problems. A research scientist should have a deep understanding of machine learning theory and strong programming skills.
5. Product manager: This role involves overseeing the development of machine learning products and ensuring they meet customer needs. A product manager should have strong communication skills, as well as technical knowledge of machine learning algorithms and applications.
6. AI Ethics Specialist: This role involves examining the ethical implications of artificial intelligence and machine learning applications, developing guidelines and principles to ensure the responsible use of AI, and overseeing compliance with regulations and standards.

There are also opportunities for machine learning professionals in various industries such as healthcare, finance, e-commerce, and more. As technology continues to advance, the demand for machine learning professionals is expected to grow, making it a promising career path for those interested in this field.

Skills Required to Become an AI and Machine Learning Professional

To become an AI and machine learning professional, you need to have a combination of technical and soft skills. Here are some of the key skills required:

1. You need to have a strong foundation in programming languages such as Python, R, Java, C++, or Matlab. These languages are widely used in developing machine learning algorithms and models.
2. You should have a good understanding of statistics, probability theory, linear algebra, and calculus. These concepts form the foundation of many machine learning algorithms.
3. You should also be familiar with various machine learning algorithms such as decision trees, neural networks, logistic regression, k-nearest neighbours, and support vector machines. Understanding the strengths and weaknesses of these algorithms is essential for building effective models.
4. You should have a good understanding of data structures, data cleaning, data transformation, and data visualisation. This is important for processing and analysing large datasets.
5. You should be familiar with popular deep learning frameworks like TensorFlow, PyTorch, and Keras. These frameworks provide an efficient way to develop and train deep neural networks.
6. You should be able to identify business problems and opportunities that can be addressed through AI and machine learning. This requires good analytical and problem-solving skills.
7. You should be able to communicate technical concepts effectively to both technical and non-technical stakeholders. This includes writing reports, creating presentations, and explaining complex concepts in simple terms.
8. The field of AI and machine learning is constantly evolving, and new techniques and algorithms are being developed all the time. As a professional, you need to have a willingness to learn and keep up with the latest advancements in the field.

By acquiring these skills, you can become a proficient AI and machine learning professional and make a career in this field.

Why You Should Choose Sunstone For Your MCA? 

Colleges powered by Sunstone offer several advantages that can enhance a student's chances of succeeding in job interviews. These include access to over 70 sessions conducted by industry experts and recruiters, opportunities to undertake capstone projects each semester, and the ability to create a professional portfolio that can attract potential employers. The faculty members at these colleges are also highly experienced, with many having worked at renowned institutions such as IIMs and IITs. These benefits provided by Sunstone can greatly improve a student's career prospects.

FAQ - Machine Learning

What are the different types of machine learning?

There are three main types of machine learning: supervised learning, unsupervised learning, and reinforcement learning. 

 What are the applications of machine learning?

Machine learning has a wide range of applications across various industries, including healthcare, finance, marketing, and more. Some common applications include fraud detection, image and speech recognition, natural language processing, recommendation systems, and predictive analytics.

What are some popular machine learning tools and frameworks?

There are several popular machine learning tools and frameworks, including Python, R, TensorFlow, PyTorch, Keras, Scikit-learn, and Apache Spark. These tools provide an efficient way to develop and train machine learning models.