Certificate Course Artificial Intelligence & ML

4 Month industry oriented course in Artificial Intelligence & Machine Learning with placement assistance and live project.

Entry Level Jobs20%
Mid Level Jobs55%
Senior Level35%
0 +
Jobs per 100

Among Top 4 Employable Skills

Why Join CC-AIML?

Certificate course in Artificial Intelligence & Machine Learning is a 4-month classroom program for fresh graduates and early career professionals looking to build their career in Artificial Intelligence & Data Sciences. Candidates from the course are able to transition to roles such as  business analysts, data analysts, data engineer, analytics engineer etc. by learning relevant AI & ML techniques, tools and technologies and hands-on application through industry case studies.

Innovative Approach

Our business analytics course offers a blended learning environment or an online learning environment that causes minimal disruptions to work schedule. Sessions are assisted by online webinars, discussions and assignments for continuous and cumulative learning.

Corporate Collaboration

Our corporate partners are deeply involved in curriculum design, facilitating projects, industry lectures, and professional evaluation.

Live Projects

Live projects allows you to apply your learning to real industry projects and add it to your portfolio for potential employers to see as a tangible body of work.

Talent Pool

Interaction in the classrooms is not just with peers but active employees from different industries who bring their unique experiences to the fore.

Program Structure

The 4-month Certificate Course uses a combination of learning methods that include classroom teaching, hands-on exercises, and sessions with industry practitioners. Classes are conducted on weekdays and are assisted by online discussions and assignments.

Classroom Learning

Classroom sessions by our industry expert faculty would be conducted from Monday to Thursday starting 9:30 AM at the Noida center.

Lab Sessions

Regular in-class lab sessions help candidates apply concepts to real-life scenarios under the guidance of a faculty and industry expert.

4-Week Project Work

Candidates work on an application-oriented industry project where they are mentored and evaluated by faculty and industry experts.


The curriculum has been designed by industry experts with the learning content and assessments created by faculties from Universities and top companies working in Data Sciences.


  • Python Basics
  • Jupyter notebook – Installation & function
  • Python functions, packages and routines
  • Pandas, NumPy, Matplotlib, Seaborn
  • Working with data structures,arrays, vectors & data frames
  • Descriptive Statistics
  • Inferential Statistics
  • Probability & Conditional Probability
  • Probability Distributions - Types of distribution – Binomial, Poisson & Normal distribution
  • Hypothesis Testing

Machine Learning

  • Multiple Variable Linear regression
  • Multiple regression
  • Logistic regression
  • K-NN classification
  • Naive Bayes classifiers
  • Support vector machines
  • K-means clustering
  • Hierarchical clustering
  • High-dimensional clustering
  • Dimension Reduction-PCA
  • Decision Trees
  • Random Forests
  • Bagging
  • Boosting
  • Introduction to Recommendation systems
  • Content based recommendation system
  • Popularity based model
  • Collaborative filtering (User similarity & Item similarity)
  • Hybrid models

Artificial Intelligence

  • Multiple Variable Linear regression
  • Multiple regression
  • Logistic regression
  • K-NN classification
  • Naive Bayes classifiers
  • Support vector machines
  • Introduction to Convolutional Neural Networks
  • Forward propagation & Backpropagation for CNNs
  • Convolution, Pooling, Padding & its mechanisms
  • CNN architectures like AlexNet, VGGNet, InceptionNet & ResNet
  • Transfer Learning
  • Bag of Words Model
  • TF-IDF
  • POS Tagging
  • Named Entity Recognition
  • Tokenization
  • Stop Words
  • Word Vectorizer
  • Introduction to Sequential data
  • RNNs and its mechanisms
  • Vanishing & Exploding gradients in RNNs
  • Time series analysis
  • LSTMs
  • LSTMs with attention mechanism
  • GRUs - Gated recurrent unit
  • Case study: Machine Translation
  • Case study: Sentiment analysis
  • Semantic segmentation
  • YOLO
  • Siamese Networks
  • Object & face recognition using techniques above
  • Introduction to GANs
  • AutoEncoders
  • How GANs work?
  • Applications of GANs
  • Value based methods Q-learning
  • Policy based methods

Languages & Tools

  • Python
  • Data libraries like Pandas, Numpy, Scipy
  • Python ML library scikit-learn
  • Python visualization library Matplotlib
  • NLP library NLTK
  • Tensor Flow
  • Keras
  • Seaborn

Placement Assistance

As a participant in this program, Hex N Bit in collaboration with Map Resume helps you unlock your potential, highlight your skills and connect to the right opportunities for your next job.

Exclusive Recruitment Drives

Attend job fairs organised every 2 months across cities. Participate in our recruitment drives with top tech companies looking for professionals like you.

Access Curated Jobs

Access a list of jobs relevant to your experience and domain. Leverage our dedicated career support team working with 200+ organisations, who’ll recommend the right jobs for you.

Interview Workshops

Familiarise yourself with commonly asked questions that’ll help you crack any technical interview. Use your ePortfolio to showcase your skills and improve your chances of getting hired.

Personalised Career Mentorship

Get an expert career mentor personalised to your experience and industry, who will help you navigate your path to career success. Get guidance on choosing the right opportunities, building a great CV and much more.



Regular Classroom Program

4 Months
  • Recommended for Non Working
  • 100+ hours of classroom sessions
  • Lab work with faculty guidance
  • 150+ Hours of Online Content

Weekend Classroom Program

6 Months
  • For Working Professionals
  • 100+ hours of classroom sessions
  • Lab work with faculty guidance
  • 150+ Hours of Online Content

Batch Details


Batch Starts - 1st November 2019