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
Potential to earn an average salary of
₹ 5 LPA to ₹ 10 LPA
IT, Healthcare, Manufacturing, Retail, Marketing, Finance and more
- Commencement Date
- Duration 658 hours
- Language English
- Eligibility Criteria Diploma completed or pursuing Bachelor’s degree in Engineering/Technology/Statistics/Mathematics/
Minimum Age: 18 Years
- Multiple intermediate assessments and one final assessment leading to certification.
- Final assessment date will be announced, 1 month in advance.
- Total Credits NA
Lecture Credits NAPractical Credits NA
- Course Format Online (Self-paced + Live Lectures + Hands-on Learning)
What you will learn in the course
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.
The course syllabus will be delivered through a combination of learning resources, live lectures and community-based interactions.
- Introduction to Artificial Intelligence and Machine Learning
- Types of Machine Learning
- Trends in Artificial Intelligence
- Importance of Python
- Introduction to Python and comparison with other programming languages
- Python basics
- Object-Oriented Programming System (OOPS)
- Basic libraries for Data Science
- Types of data and ways to measure data
- Basics of Probability
- Basics of Statistics
- Basics of Calculus and Linear Algebra
- 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
- Linear regression
- Logistic regression
- Polynomial regression
- Support vector regression
- Decision tree regression
- Random forest regression
- Linear models
- Non-linear models
- Model evaluation
- K-means clustering
- Density-based clustering
- Distribution model-based clustering
- Hierarchical clustering
- Fuzzy clustering
- Apriori algorithm
- Dimensionality reduction
- Hyperparameter tuning
- Introduction to Deep Learning
- Introduction to Natural Language Processing
- Image processing
- Recommendation systems
Meet the Mentor(s)
Devesh Chandra Lal
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 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.
- 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.
- 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.
- 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.
- The programme includes online live sessions, recordings of live sessions, reading materials, community-based interactions and hands-on learning experience.
- 70% attendance for scheduled live lecture sessions on the learning platform is mandatory.
- 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.
- 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. If the learner is not able to clear the exam in the second attempt, he/she will have to purchase the programme again.
- 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.
- 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.
- 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.
- Once the payment is made, no refund will be issued under any circumstances.