Complete Guide to Machine Learning and Artificial Intelligence

Solve Real-World Problems with Machine Learning and AI

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Make a life-changing career decision now!

Career opportunities in AI and ML are growing rapidly as the world is becoming more and more dependent on data. The data-driven operations, adopted by almost every industry, will increase the demand for well-trained AI and ML professionals.

Potential Job Opportunities

22,000+ jobs listed across various industries
Earning Potential

Potential to earn an average salary of ₹ 5 LPA to ₹ 10 LPA
Employment Sector

IT, Healthcare, Manufacturing, Retail, Marketing, Finance and more

Potential Career Path

Data Analyst

Data Engineer

Data Scientist

Related Courses

Course Details

Commencement Date
Duration 658 hours
Language English

Eligibility Criteria Diploma completed or pursuing Bachelor’s degree in Engineering/Technology/Statistics/Mathematics/Computer Science
Minimum Age: 18 Years
Assessment
- Multiple intermediate assessments and one final assessment leading to certification.
- Final assessment date will be announced, 1 month in advance.
- NA
- NA

Total Credits NA
Lecture Credits NA

Practical Credits NA
Course Format Online (Self-paced + Live Lectures + Hands-on Learning)

Learning and Assessment Centre

What you will learn in the course

Differentiation between supervised and unsupervised machine learning methods

Supervised learning algorithms, including classification and regression

Unsupervised learning algorithms, including clustering and dimensionality reduction

Statistical modeling related to machine learning and its comparison

Using state-of-the-art Deep Learning frameworks such as Google’s TensorFlow

Applications of Deep Learning in image recognition, NLP, and so on

Course Summary

According to recently updated International Data Corporation (IDC) Worldwide Artificial Intelligence Systems Spending Guide, the spending on AI systems will reach USD 282 billion by 2027. Globally, vendors of consumer devices such as phones, speakers, displays, wearables, and the like, are competing and investing billions to make their devices feature-rich, more powerful, connected and affordable. Professionals who are pursuing a career in Machine Learning and Artificial Intelligence will be progressively in demand as companies continue to adopt AI and ML innovations in the coming decade.

The objective of the programme is to enable the learners to acquire knowledge on Machine Learning (ML), Deep Learning, Natural Language Processing (NLP), Computer Vision and different algorithms to build custom ML models, facilitate better understanding of conversational experiences and create better customer experience.

Course Syllabus

The course syllabus will be delivered through a combination of learning resources, live lectures and community-based interactions.

Module 1: Introduction to Machine Learning

Introduction to Artificial Intelligence and Machine Learning
Types of Machine Learning
Trends in Artificial Intelligence
Importance of Python

Module 2: Python for Artificial Intelligence

Introduction to Python and comparison with other programming languages
Python basics
Functions
Object-Oriented Programming System (OOPS)
Basic libraries for Data Science

Module 3: Probability and Statistics

Introduction
Types of data and ways to measure data
Basics of Probability
Basics of Statistics
Basics of Calculus and Linear Algebra

Module 4: Exploratory Data Analysis

Preprocessing data in Python
Dealing with missing values in Python
Data formatting in Python
Handling imbalanced data
Handling outliers
One-hot encoding and label encoding
Feature engineering and selection

Module 5: Supervised Machine Learning

Linear regression
Logistic regression
Polynomial regression
Support vector regression
Decision tree regression
Random forest regression
Linear models
Non-linear models
Model evaluation

Module 6: Unsupervised Machine Learning

K-means clustering
Density-based clustering
Distribution model-based clustering
Hierarchical clustering
Fuzzy clustering
Apriori algorithm
Dimensionality reduction
Hyperparameter tuning

Module 7: Advanced Artificial Intelligence

Introduction to Deep Learning
Introduction to Natural Language Processing
Image processing
Recommendation systems

View Full Syllabus Download Syllabus

*Modules are subject to change based on Academic Partner’s discretion; learners will be informed of the ﬁnal curriculum during the orientation.

Course Features

Digital Learning Resources

Enriching learning resources accessible anytime and anywhere

Live Lectures

Live lectures delivered by Academic Experts

Academic Connect Community

Moderated by an Academic Expert with a focus on building conceptual clarity

Industry Connect Community

Moderated by an Industry Expert with a focus on building industry-oriented applied knowledge

Industry Assignments

Access to projects to offer industry-relevant practical exposure to learners

Intermediate Assessments

Continuous check for skills competency highlighting scope for improvement

Final Assessment

End-term test of theoretical and applied knowledge

Digital Certification

Certificate issued by Academia and Industry on successful completion of the learning programme

Internship Opportunity

To provide on-the-job real-time industry exposure for learners in the respective learning programmes

Job Opportunity

Access to TCS iON Job Listing Portal - a hub of employment opportunities across sectors

Digital Learning Resources Enriching learning resources accessible anytime and anywhere
Live Lectures Live lectures delivered by Academic Experts
Academic Connect Community Moderated by an Academic Expert with a focus on building conceptual clarity
Industry Connect Community Moderated by an Industry Expert with a focus on building industry-oriented applied knowledge
Industry Assignments Access to projects to offer industry-relevant practical exposure to learners
Intermediate Assessments Continuous check for skills competency highlighting scope for improvement
Final Assessment End-term test of theoretical and applied knowledge
Digital Certification Certificate issued by Academia and Industry on successful completion of the learning programme
Internship Opportunity To provide on-the-job real-time industry exposure for learners in the respective learning programmes
Job Opportunity Access to TCS iON Job Listing Portal - a hub of employment opportunities across sectors

Meet the Mentor(s)

Devesh Chandra Lal

Manager (IT)

CRISP, Bhopal

Devesh Chandra Lal has completed BCA and Diploma in Production Engineering and holds a professional certification from Microsoft and CISCO. He has a rich experience of 26 years in the field of IT, Networking and CISCO training and has been awarded as one of the best trainers for “CISCO Instructors” in Asia Pacific Region.

Ritu Shukla

Consultant Trainer

CRISP, Bhopal

Ritu Shukla is currently working as a Consultant Trainer in the Department of IT, CRISP, Bhopal. She holds a Master’s degree in Computer Engineering from University of Mumbai, a Postgraduate Diploma in Data Science and Artificial Intelligence from IIIT, Delhi, and a Postgraduate Diploma in Environmental Management. She has 8+ years of experience in industry as well as in the educational field. Her area of expertise lies in Machine Learning and Artificial Intelligence.

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FAQs

1. What is the application process for the programme? +

Candidates must apply on OR before the application closure date.
Verification of candidate details will be done by Academic Partner.
If the application is approved, candidates will receive an approval notification via email.
In case the application gets rejected; candidates will not be able to enrol for the course.
If there is any information missing in the application form, candidates would be asked to edit/fill the application form with missed out information and resubmit.
Approved candidates will receive the Activation Code from their respective institutions to activate the course.
The learning programme will be added to learner’s dashboard subject to successful payment and activation.

2. Who should join this programme and how will this help learners in building their proficiency? +

Students who have completed diploma or undergraduate courses, freshers, hobbyists, working professionals who want to upskill or cross-skill are eligible to join this learning programme.
Learners will gain knowledge on concepts and algorithms used in Machine Learning and Artificial Intelligence.

3. I am not from an IT domain. Can I take up this programme? +

Yes. The need for AI and Data Science is rapidly spreading across all domains. The prerequisite for this programme is knowledge of Grade 12 Mathematics.

4. What will be the teaching-learning method for this programme? +

The programme includes online live sessions, recordings of live sessions, reading materials, community-based interactions and hands-on learning experience.

5. What is the attendance policy? +

70% attendance for scheduled live lecture sessions on the learning platform is mandatory.

6. If I am unable to progress with the learning due to critical reasons, can I complete my certifications at the later stage? +

It is recommended to complete the programme during the scheduled time period. In case of any break in the learning progress, learner will need to purchase the programme again.

7. How am I assessed and what is the process for re-examination? +

The programme includes two sets of assessments - Intermediate and Final.

Intermediate Assessments: These are module-wise assessments, quizzes/assignments that are planned at regular intervals through the entire programme duration. The end of module exams have no weighatge in the final summative score of this programme.
Final Assessment: Final assessment will be conducted at the end of the learning programme.

Learners need to secure minimum 70% of marks to pass the final assessment (both in theory and practical).
Learners will get two attempts to clear the final exam. An exam fee will be applicable for the second attempt.

8. What are the criteria to obtain a certificate? +

Learners should have completed 70% attendance for live lectures.
Completion of all module nodes (inclusive of internal assessments and assignments).
Successful completion of summative/final assessment and projects (as applicable).
The following is the performance grade structure for the final assessment for this programme:

85% and Higher: Grade A
80% to < 84.99%: Grade B
70% to < 79.99%: Grade C
0.0% to < 69.99%: Grade D - Fail

Learners who have not cleared/appeared for the summative assessments can reappear for the same. Candidates will be provided total of 2 attempts to clear the summative exams.

9. How will this programme make me job ready? +

This programme is designed in consultation with our academic and industry SMEs to ensure that the skills and competencies covered are relevant and makes the learner job ready.
The programme emphasises on both conceptual and hands-on practice and complimented with internship opportunities in industry, as applicable.
In addition to the programme certificate, learners can also opt for TCS iON National Qualifier Test (NQT) from TCS iON to enhance their job accessibility. TCS NQT score is a validation of their cognitive and aptitude skills.

10. Is there any internship opportunity through this programme? Will I be placed in the same company from where I pursued my internship? +

Remote or On-site internship opportunities, will be made available as applicable. This is subject to available opportunities and policies of the companies.
Access to employment opportunities is subject to available vacancies and hiring policies of the companies.

11. What is the refund policy for the programme? +

Once the payment is made, no refund will be issued under any circumstances.

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