Business Toys
700+
Upskilled
Online
mode
110 Hours
Duration
June 20, 2020
Start Date
97%
Success rate
Apply Now
Online
mode
June 20
Start Date
Apply Now
Data Science Project Training
Python, Tableau, R Programming, Excel, Keras, Hive, MySQL, MongoDB, Hadoop, Spark, Jupyter, Heroku
Brochure
Enroll
Enroll
700+
Upskilled
Online
Mode
110+
Duration
June 20
Start Date
97%
Success Rate
Online
Mode
June 20
Start Date
10+
Technologies
Request a demo
Estimated Time
4 Months
Enrolled By
Dec 15, 2019
Prerequisites
See prerequisites in detail
Estimated Time
4 Months
Enrolled By
Dec 15, 2019
Prerequisites
See prerequisites in detail
About Data Science Project Training
Introduction
In the competitive career environment for jobs in Data Science, Machine Learning & AI it is difficult for job seekers to demonstrate the practical experience & differentiate themselves with others. Moreover, experienced professionals with software development backgrounds are expected to have end-to-end data science project implementation experience.
This course is specifically customized and tailor-made to cater to the above requirements with broad coverage of all the software tools, frameworks, and skills. These skills are required for one to feel more confident to answer Data Science Interview questions for both Junior as well as senior positions and to make a quick transition to Data Science Profiles.
4End-to-End projects
16+in Demand technologies
25hrAverage project length
Key benefits
Exposure to multiple project domains like E-Commerce, Telecom, Healthcare etc.
Real time proprietary end-to-end projects & training from Industry practitioners
Online Instructor led session
Flexible schedule during non-working hours
Peer discussion & brainstorming
Dedicated mentoring support
Resume optimization & Interview preparation
Brushing up of all key concepts with use cases
Exposure of end-to-end technologies used in Data Science
Access to recorded sessions for every class
Session consistency & regular evaluation with assignments
Easy payment & EMI options
Who should take this
  1. Self-learners needing a structured learning path
  2. Working professionals with similar line of experience
  3. Working professionals with previous relevant experience
  4. Students & professionals having done certifications but not project experience
  5. Professionals seeking crash-course in Data Science on fast-track learning mode
Level-Up with personalized services
We offer personalized services as per your needs at every stage of your learning journey to ensure you succeed.
Target career profiles
Project domains coverage
Tools & software frameworks
Techniques & Models
What type of Job profile you can target?
Machine Learning Engineer
Data Scientist
NLP Expert
OpenCV Expert
Data Science Lead
Analytics Manager
Data science solution architect
Target career profiles
What type of Job profile you can target?
Machine Learning Engineer
Data Scientist
NLP Expert
OpenCV Expert
Data Science Lead
Analytics Manager
Data science solution architect
Project domains coverage
Which domain projects you will build?
E-commerce
Telecom
Healthcare
Consumer & Retail
Media & Entertainment
Technology
Tools & software frameworks
What technologies you will learn?
Techniques & Models
What models you will build?
ETL
Applied Statistics
Applied Mathematics & Linear Algebra
Supervised Machine Learning
Unsupervised Machine Learning
Deep learning
Neural Networks – ANN/ CNN / RNN
Natural Language Processing
OpenCV
What you will learn
PHASE – I: Pre-assessment & feedback
See More
  1. Pre-assessment task – I: Data Extraction using SQL
  2. Pre-assessment task – II: Applied Statistics using R/Python
  3. Pre-assessment task – III: Applied Machine Leaning using Python
  4. Pre-assessment task – IV: Applied Deep Learning
  5. Individual feedback and discussion.
Note: Pre-assessment is a part of project training where students will be assigned different tasks as mentioned above and are expected complete the same within given deadline. During the instructor led session, students will be given individual feedback and overall feedback will be share with team Nirvana.
PHASE – II: SQL, Statistics, ML & DL Primer
See More
  1. Complete overview of SQL
  2. Applied Statistics – Case studies on Descriptive & Inferential statistics
  3. Machine Learning – Overview of supervised and unsupervised algorithms
  4. Deep Learning – Introduction & overview
Note: Above concepts will be covered purely though use case applications to provide an overview of concepts. Our team will provide feedback to Nirvana coordinator in case any topic needs to be covered in detail.
PHASE – III: Life Cycle of Data Science Projects
See More
  1. Data sourcing - Web Scrapping, Third Party API Connections, Big Data Frameworks.
  2. Feature engineering: Imputation and its types, Handling Imbalanced datasets, removing noise, data restructuring, data cleaning, data normalization, handling categorical features.
  3. Feature selection: Pearson correlation, Heatmaps, Extra tree classifiers, etc.
  4. Model building: Model selection, hyper parameter optimization & tuning.
  5. Model evaluation: Evaluation techniques for Regression & Classification
  6. Production & deployment: Introduction to model deployment frameworks like FLAST, AZURE, AWS, etc. and generating REST API.
PHASE – IV: Project Execution
See More
Projects pertaining to following domains will be delivered to the students:
  1. Consumer & Retail/Media & Entertainment
    • Determination Customer Lifetime Value (CLV)
    • Customer churn modeling
    • Product Merchandizing
    • Music Recommendation engine for cloud music app
  2. E-Commerce
    • Data Driven Business Strategy
    • Customer retention & success
    • Recommendation Engine
    • Elastic search & Review classification
    • Building online chatbot
  3. Finance
    • Credit Card Fraud Detection
    • Stock price prediction
    • Fake news detection
  4. Healthcare
    • Heart disease detection
    • Cancer detection
    • Detection of Parkinson’s disease
  5. Technology
    • Natural language Processing – Issue extraction
    • Computer vision – Image forgery OR Branding
    • Speech Analytics – Customizing Alexa
    • Speech Analytics – Emotions detection
PHASE – V: Assistance on Capstone Projects
PHASE – VI: Resume Review & project-based Interview preparation
See More
After successful completion of projects our team will help students to review their projects and also train them on answering interview questions based on projects they have undertaken.
How can I join?
Enquire
Online Demo
Get Mentored
Get Enrolled
Enquire
Step 1
Online Demo
Step 2
Get Mentored
Step 3
Get Enrolled
Step 4
Total Investment : $  USD. 800
Total Investment
$  USD. 800
EMI Plans
Registration
Percent
Easy EMI with 0% 
interest
On registration
10%
1st installment - 1st month of joining
1st installment 1st month of joining
70%
2nd installment - 2nd month of joining
2nd installment 2nd month of joining
20%
Register Now

Still confused where to start?

Hear is how we can help you:

Resume feedback
One-to-One career mentoring
Online Live Demo sessions
Guidance on career transitions
Walk-through program schedule
Frequently Asked Questions
    Career prospects & support
      How will this program help me get a job in Data Science?
      Upskilling: Primarily, our mentors and experts continuously put efforts in building participants resume by imparting right skills which are required for targeted job profiles via projects. Resumes are optimized so that search appearances for relevant search on job search portals increase. Students are also well prepared for their interviews via personal mentoring and providing interview questions.
      Access to opportunities
      Our HR team continuously work in tracking companies who are in hunt on candidates of desired profiles. Resumes of participants are then circulated to these potential recruiters increasing their chances of getting jobs.
More questions? FAQ