Full-Stack Data Scientist course is aimed towards helping you to learn the full cycle of identifying the business problem, analyzing the data sources and decoding if more data is needed, transform the data so that it can be put into an ML algorithm, training the models, measuring how well the models solve the business problem, and its implementation.
As a Full-Stack Data Scientist, you’ll be responsible for handwritten digits identification, building a recommendation engine, practical case study on Banking Data, classifying the type of cancer case study, object detection in the live video feed, webcams, video files on youtube, sentimental analysis for review. The Full-Stack Data Scientist training and certification course teach you all of it.
- Full-Stack Data Scientist online and classroom training programs every weekend
- Proper guidelines and hacks to deal with Data Science
- Free practice tests and study materials
- Trainers with 12+ years of industry experience
- Avail Scholarship up to 80% from Global Skill Development Council
GSDC Scholarship Assessment Program:
Global Skill Development Council, The provider of this certification is currently offering Scholarship Assessment Program where you have to complete the Assessment test and earn up to 80% scholarship from Global Skill Development Council for this Full Stack Data Scientist Training & Certification program.
The Standard price for Certified Full Stack Data Scientist Certification & Training cost is $ 1300/-
The discounted pricing structure for GSDC Full Stack Data Scientist Scholarship is as follows: Apply to this Scholarship
Structure of Full-Stack Data Scientist
This Full-Stack Data Scientist training and certification course includes a total of 3 certifications with training for Certified Business Analytics Practitioner, Certified Machine Learning Master, Certified DevOps Engineer.
Full-Stack Data Scientist course curriculum is mainly focused on sharing in-depth knowledge about:
- Building telecom churn management case study
- Handwritten digits identification
- Building a recommendation engine
- Practical case study on banking data
- Classifying cancer- case study
- Object detection in the live video feed, webcams, video files or YouTube
- Sentiment Analyzer for reviews
1. Product management (BA)
- Business Analysis & Stakeholders Overview
- Communication, Planning, Evaluation, Prioritization
- BA Tools Overview & Design Documents
- Stakeholder management BPMN, Requirement Elicitation & Management
- Enterprise Analysis, Agile & Scrum
- SQL & NoSQL Databases
- MySQL deep dive
- Stream processing
- Batch processing
- Data pipelines
- Big data technologies
- Spark and Hadoop
- Python for data science
- Detailed Python curriculum — required for data science
- Data Analytics Libraries
- Data Visualization — matplotlib, seaborn, plotly
- Exploratory Data Analysis
- Overview of Data Science
- Business problem understanding
- Statistics for Data Science [need to be detailed]
- Machine Learning Overview and Techniques
- Supervised Machine Learning
- Algorithms — Linear Regression, Logistic Regression, Decision, Random forest, SVM
- Unsupervised Machine Learning — clustering algorithms
- AI and Data Science
- ANN, RNN, CNN Overview
- Deep learning overview
- Monitoring, Reliability
- Microservice architecture
- Tools for model deployment
- Continuous integration and deployment — jenkins
- AWS Overview & Important AWS services
- Machine Learning Model Deployment on AWS
Professionals who belong to the following fields are eligible to take up the Full Stack Data Scientist course:
- IT Service Managers
- Project & Program Managers
- Business Analysts
- Testing Professionals
- Data Center Professionals
- Release Managers
- Change Managers
- System Architects
- System Engineers
- Project Managers, Program Managers, Delivery Manager
- Software Developers/ Team Leaders
- Business Development/Sales executives
- Customer Service Representatives
- Quality Assurance
- Subject Matter Expert in IT/KPO/BPO
- Web Developers
- Application Developers
Training Delivery Style:
This Full Stack Data Scientist training focuses on experiential learning. The material of this course is divided into interactive sessions.
Not only this, if you are participating, expect yourself to get indulged with interesting group activities. By this, you will get a chance to put the theory into action.
This training will be nothing like any ordinary training you imagine. We follow a vast range of creative methodology which will allow you to wrack your grey matter and boost your energy up to participate.
The key features of our training program would be:
- Training sessions in a storytelling format
- Exhibition of concepts with the help of professional examples
- Self-analysis and group discussions
- Case studies as the application of the concepts which were taught
- Vibrant presentations along with individual and team activities
- Post-training reading suggestions
Benefits of Full-Stack Data Scientist Training:
- Helps in gaining expertise in Product Management, Data Engineering, Machine Learning, Backend Engineering, and DevOps
- Covers the ML project lifecycle
- Invests in software engineering
- Along with skilling you up in with technicalities, it helps you in gaining knowledge of other fields too.
Full-Stack Data Scientist Examination has 3 steps:
- Firstly, you’d need to complete your Business Analytics Practitioner Certification.
- Then, you will have to go for Certified Machine Learning Master Certification.
- At last, you’ll finish off with your DevOps Engineer Certification.
After the completion of these 3 certifications, you’ll be announced as a certified Full Stack Data Scientist and will be rewarded with a certificate and badge as well.
Full-Stack Data Scientist training is conducted by accredited trainers. Trainers for this course are highly experienced professionals with more than 10 years of industry experience. Currently, they are serving in multinational companies and have trained more than 5000 professionals.
Originally published at https://www.novelvista.com.