

IBM Certified Online Data Science Course with 100% Placements
*Data Science ranks first among the top trending jobs on LinkedIn. The future is all about Data Science & Artificial Intelligence which is helping businesses in making better decisions, tools, and a better life.
Businesses are embracing Data Science in their everyday life in order to add value to every aspect of their operations. This has led to a substantial increase in the demand for Data Scientists who are skilled in advanced technologies. it is VILT & ILT training!
Data Science is one of the most booming sectors in the 21st century. Every sector – Cancer detection, paralysis detection, fraud and risk detection in banks, behavior analysis, Industry Automation is seeing a transformation.
Therefore, be a part of this Data Science revolution with Innomatics Research Labs
PREREQUISITES:
The candidate must be pursuing a Bachelor’s degree.
Previous coding experience is an added benefit.
Languages & Tools covered in IBM Certified Data Science








IBM Certified Data Science Course Curriculum (Syllabus)
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Module 6: Machine Learning Unsupervised Learning
- Why Unsupervised Learning
- How it Different from Supervised Learning
- The Challenges of Unsupervised Learning
Principal Components Analysis
- Introduction to Dimensionality Reduction and its necessity
- What Are Principal Components?
- Demonstration of 2D PCA and 3D PCA
- Eigen Values, EigenVectors, and Orthogonality
- Transforming Eigen values into a new data set
- Proportion of variance explained in PCA
Case Study: A Case Study on PCA using Python
K-Means Clustering
- Centroids and Medoids
- Deciding the optimal value of ‘K’ using Elbow Method
- Linkage Methods
Hierarchical Clustering
- Divisive and Agglomerative Clustering
- Dendrograms and their interpretation
- Applications of Clustering
- Practical Issues in Clustering
Case Study: A Case Study on clusterings using Python
Association Rules
- Market Basket Analysis
Apriori
- Metric Support/Confidence/Lift
- Improving Supervised Learning algorithms with clustering
Case Study: A Case Study on association rules using Python
CAPSTONE PROJECT: A project on a use case will challenge the Data Understanding, EDA, Data Processing, and Unsupervised algorithms.
RECOMMENDATION SYSTEMS
- What are recommendation engines?
- How does a recommendation engine work?
- Data collection
- Data storage
- Filtering the data
- Content-based filtering
- Collaborative filtering
- Cold start problem
- Matrix factorization
- Building a recommendation engine using matrix factorization
- Case Study
Module 7: Deep Learning
Introduction to Neural Networks
- Introduction to Perceptron & History of Neural networks
- Activation functions
- a)Sigmoid b)Relu c)Softmax d)Leaky Relu e)Tanh
- Gradient Descent
- Learning Rate and tuning
- Optimization functions
- Introduction to Tensorflow
- Introduction to Keras
- Backpropagation and chain rule
- Fully connected layer
- Cross entropy
- Weight Initialization
- Regularization
TensorFlow 2.0
- Introducing Google Colab
- Tensorflow basic syntax
- Tensorflow Graphs
- Tensorboard
Artificial Neural Network with Tensorflow
- Neural Network for Regression
- Neural Network for Classification
- Evaluating the ANN
- Improving and tuning the ANN
- Saving and Restoring Graphs
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Module 8: Computer Vision
Working with images & CNN Building Blocks
- Working with Images_Introduction
- Working with Images – Reshaping understanding, size of image understanding pixels Digitization,
- Sampling, and Quantization
- Working with images – Filtering
- Hands-on Python Demo: Working with images
- Introduction to Convolutions
- 2D convolutions for Images
- Convolution – Backward
- Transposed Convolution and Fully Connected Layer as a Convolution
- Pooling: Max Pooling and Other pooling options
CNN Architectures and Transfer Learning
- CNN Architectures and LeNet Case Study
- Case Study: AlexNet
- Case Study: ZFNet and VGGNet
- Case Study: GoogleNet
- Case Study: ResNet
- GPU vs CPU
- Transfer Learning Principles and Practice
- Hands-on Keras Demo: SVHN Transfer learning from MNIST dataset
- Transfer learning Visualization (run package, occlusion experiment)
- Hands-on demo T-SNE
Object Detection
- CNN’s at Work – Object Detection with region proposals
- CNN’s at Work – Object Detection with Yolo and SSD
- Hands-on demo- Bounding box regressor
- #Need to do a semantic segmentation project
CNN’s at Work – Semantic Segmentation
- CNNs at Work – Semantic Segmentation
- Semantic Segmentation process
- U-Net Architecture for Semantic Segmentation
- Hands-on demo – Semantic Segmentation using U-Net
- Other variants of Convolutions
- Inception and MobileNet models
CNN’s at work- Siamese Network for Metric Learning
- Metric Learning
- Siamese Network as metric learning
- How to train a Neural Network in Siamese way
- Hands-on demo – Siamese Network
Module 9: Natural Language Processing (NLP)
Introduction to Statistical NLP Techniques
- Introduction to NLP
- Preprocessing, NLP Tokenization, stop words, normalization, Stemming and lemmatization
- Preprocessing in NLP Bag of words, TF-IDF as features
- Language model probabilistic models, n-gram model, and channel model
- Hands-on NLTK
Word Embedding
- Word2vec
- Golve
- POS Tagger
- Named Entity Recognition(NER)
- POS with NLTK
- TF-IDF with NLTK
Sequential Models
- Introduction to sequential models
- Introduction to RNN
- Introduction to LSTM
- LSTM forward pass
- LSTM backdrop through time
- Hands-on Keras LSTM
Applications
- Sentiment Analysis
- Sentence generation
- Machine translation
- Advanced LSTM structures
- Keras – machine translation
- ChatBot
Module 10: Tableau for Data Science
Tableau for Data Science
- Install Tableau for Desktop 10
- Tableau to Analyze Data
- Connect Tableau to a variety of dataset
- Analyze, Blend, Join and Calculate Data
- Tableau to Visualize Data
- Visualize Data In the form of Various Charts, Plots, and Maps
- Data Hierarchies
- Work with Data Blending in Tableau
- Work with Parameters
- Create Calculated Fields
- Adding Filters and Quick Filters
- Create Interactive Dashboards
- Adding Actions to Dashboards
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Key Features of Online Data Science Training
Flexible Timings

Flexible timings for working professionals
24/7 support

24/7 One-to-one Mentorship Support
Flexible payments

Flexible Payments with Easy Installments
Life-Time Access

Life time Free access to Workshops & Seminars
For any queries feel free to Call/WhatsApp us on +91 9951666670 or mail at [email protected]
We provide Self-paced training on IBM Certified Data Science course for individuals who are occupied with work and want to learn in their free time. We are giving lifetime access to self-paced learning. Our Self-paced video duration has 100 – 120 Hrs with Real-time practical sessions and Assignments. We are available round the clock on WhatsApp, Emails, or Calls for clarifying doubts and instance assistance.
For any queries feel free to call/WhatsApp us at 91 9951666670 or mail at [email protected]
For any queries feel free to call/WhatsApp us on +91 9951666670 or mail at [email protected]
For any queries feel free to call/WhatsApp us on +91 9951666670 or mail at [email protected]
Advantages of Online Data Science course training?
By associating with Innomatics Research Labs, you will:
- Gain comprehensive end-to-end knowledge
- Build a strong foundation in Data Science & Data Analytics
- Gain knowledge about industry-standard tools and techniques
- Enjoy a practical-oriented teaching methodology
- Gain knowledge and understanding of statistical techniques critical to Data Analysis & Analytic models
Who Can Enrole For This Online Data Science Course?
This Data Science Course is specifically ideal for people who are
- Freshers who want to start the career as we teach from the basics and gradually build up your skills.
- Individuals who are graduated and working in the Data Science technology field and looking to upgrade career.
- Analysts and Software engineers looking for a career shift in the data science stream.
Job opportunities in Data Science

Key Highlights of Online Data Science Program
- 500+ Industry experts from fortune 500 companies
- Dedicated In-house data scientist team accessible round the clock
- 200+ Hours of intensive practical oriented training
- Flexible Online training sessions
- 5+ Parallel Online Data science batches running currently on both weekdays & weekends
- Backup Classes and Access to the Learning Management System (LMS)
- One-to-One Mentorship and Free Technical Support
- FREE Data science Internship on our projects & products
- Projects and use-cases derived from businesses
- 30+ POCs and use cases to work, learn, and experiment
- Bi-weekly Industry connects from industry experts from various sectors
- Opportunity to participate in meet-ups, hackathons, and conferences
- Dedicated training programs for NON-IT professionals
- 100% placement assistance
- Globally Recognized Certification from IBM

Here are the Success Stories of our Innominions
Frequently Asked Questions (FAQs) on Online Data Science Course
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Why choose an online data science course?
The best reason one could say to choose online data science course that is specially provided by innomatics is due to the flexibility of it. The online course for data science is so intuitive that you will enjoy it while doing it. Another thing is the convenience of learning at your home with the same quality that could be on-campus.
How are Innomatics verified certificates awarded?
Upon completion of the program, we will conduct the assessment, hackathons, assignments and based on the qualification in the assessment, trainees will be awarded the certification from IBM. This is a globally recognized certificate that will include over top MNCs from around the world.
What are the benefits of Innomatics self-paced Training?
Innomatics offers self-paced training to those who wants to learn at their own pace, This provides includes lifetime access to LMS where the trainees can see the backup classes, one-one sessions and queries through email. There would be an arrangement of virtual live class sessions for the trainees as well.
What do i need to do if I want to switch from self-paced training to instructor-led training?are Innomatics verified certificates awarded?
At Innomatics, the trainee can learn based on their comfort level. One can easily switch from self-paced to online instructor-led training without any extra effort.
What is the other mode so draining available at Innomatics?
Innomatics also provide Classroom Data Science Training, Online Data Science Training and Corporate Training for the employees which can upskill the workforce.
Will there be any support provided if I need assistance on the projects?
Innomatics trainers would round-the-clock and here to provide 100% assistance for all the queries that trainee raise. We are available through email or call and can also arrange a one-one session with the trainer if needed.
Do you provide any placement assistance?
Innomatics help trainees to achieve their dreams by helping trainees finding potential recruiters, resume busking, mockup interviews and helping with the entire recruiting process.
How can I choose the best specialization?
Innomatics will provide the trainees with the options that best suit them based on their background. We would suggest the best based on the role and interests. We will suggest the below based on the roles.
Data Engineering:Software and IT Professionals
Deep Learning: Engineers, Software and IT Professionals
Natural Language Processing: Engineers, Software and IT Professionals
Business Analytics: Engineers, Managers, Marketing and Sales Professionals, Domain Expert
Business Intelligence/ Data Analytics: Engineers, Marketing and Sales Professionals, Freshers