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Aim for a successful career as a certified data scientist by enrolling in Intellipaat’s Master’s in Data Science in the USA. Through this course, you will master SQL, MongoDB, etc. The MS in Data Science course curriculum, with 24/7 support provided by our experts, aims to make you skilled in the field. You will also be working on real-time projects to gain hands-on experience.
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Course PreviewTo master data science end-to-end, you will go deep into the domain and gain expertise in concepts such as statistical computing, tableau, deep learning in AI, Keras API, real-time analytics, and many others.
No prior skills are required to apply for this Data Science Master’s program in the USA.
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Nishkam Shivam is a senior data scientist in analytics and AI at Bristlecone. He has more than nine years of experience in this field and has also worked in renowned companies like Accenture, Walmart, Emeritus, and many more.
He has over 15 years of expertise handling various analytics projects, using several ML algorithms in multiple business domains. He has extensive knowledge of SAS, SQL, R, and Python and is proficient in big data environments.
Develops high-quality applications, apart from designing and implementing scalable code.
Investigates reported problems in the quality of data and comes up with solutions to fix them.
Deploys models in SageMaker and use Lambda functions and API Gateway to integrate machine learning models in web applications.
Understands the data, data cleansing, data transformation, analyzes outcomes, and presents the result in the form of reports and dashboards.
Uses advanced statistical techniques and tools to understand operating behavior and create algorithms with advanced prescriptive and descriptive methods.
Designs and develops various machine learning models to help in deriving intelligence for business products.
Data Science with R
Python for Data Science
Machine Learning
Artificial Intelligence
Spark
Power BI
Data Blending
Advanced Excel
MongoDB
T-SQL
Database objects
MS-SQL
$702
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39 Hours 14 Module
PreviewModule 01 – Introduction to Data Science using Python
Module 02 – Python basic constructs
Module 03 – Maths for DS-Statistics and Probability
Module 04 – OOPs in Python (Self-paced)
Module 05 – NumPy for mathematical computing
Module 06 – SciPy for scientific computing (Self-paced)
Module 07 – Data manipulation
Module 08 – Data visualization with Matplotlib
Module 09 – Machine Learning using Python
Module 10 – Supervised learning
Module 11 – Unsupervised Learning
Module 12 – Python integration with Spark (Self-paced)
Module 13 – Dimensionality Reduction (Self-paced)
Module 14 – Time Series Forecasting (Self-paced)
32 Hours 9 Module
PreviewModule 01 – Introduction to Machine Learning
Module 02 – Supervised Learning and Linear Regression
Module 03 – Classification and Logistic Regression
Module 04 – Decision Tree and Random Forest
Module 05 – Naïve Bayes and Support Vector Machine (Self-paced)
Module 06 – Unsupervised Learning
Module 07 – Natural Language Processing and Text Mining (Self-paced)
Module 08 – Introduction to Deep Learning
Module 09 – Time Series Analysis (self-paced)
32 Hours 13 Module
PreviewModule 01 – Introduction to Deep Learning and Neural Networks
Module 02 – Multi-layered Neural Networks
Module 03 – Artificial Neural Networks and Various Methods
Module 04 – Deep Learning Libraries
Module 05 – Keras API
Module 06 – TFLearn API for TensorFlow
Module 07 – DNNS (deep neural networks)
Module 08 – CNNS (convolutional neural networks)
Module 09 – RNNS (recurrent neural networks)
Module 10 – GPU in deep learning
Module 11 – Autoencoders and restricted boltzmann machine (rbm)
Module 12 – Deep learning applications
Module 13 – Chatbots
24 Hours 9 Module
PreviewModule 01 – Introduction to Power BI
Module 02 – Data Extraction
Module 03 – Data Transformation – Shaping and Combining Data
Module 04 – Data Modelling and DAX
Module 05 – Data Visualization with analytics
Module 06 – Power BI Service (Cloud), Q&A, and Data Insights
Module 07 – Power BI Settings, Administration & Direct Connectivity
Module 08 – Embedded Power BI with API & Power BI
Module 09 – Power BI Advance & Power BI Premium
42 Hours 15 Module
PreviewModule 01 – Introduction to Data Science with R
Module 02 – Data Exploration
Module 03 – Data Manipulation
Module 04 – Data Visualization
Module 05 – Introduction to Statistics
Module 06 – Machine Learning
Module 07 – Logistic Regression
Module 08 – Decision Trees and Random Forest
Module 09 – Unsupervised Learning
Module 10 – Association Rule Mining and Recommendation Engines
Module 11 – Introduction to Artificial Intelligence
Module 12 – Time Series Analysis
Module 13 – Support Vector Machine (SVM)
Module 14 – Naïve Bayes
Module 15 – Text Mining
24 Hours 23 Module
PreviewModule 01 – Entering Data
Module 02 – Referencing in Formulas
Module 03 – Name Range
Module 04 – Understanding Logical Functions
Module 05 – Getting started with Conditional Formatting
Module 06 – Advanced-level Validation
Module 07 – Important Formulas in Excel
Module 08 – Working with Dynamic table
Module 09 – Data Sorting
Module 10 – Data Filtering
Module 11 – Chart Creation
Module 12 – Various Techniques of Charting
Module 13 – Pivot Tables in Excel
Module 14 – Ensuring Data and File Security
Module 15 – Getting started with VBA Macros
Module 16 – Ranges and Worksheet in VBA
Module 17 – IF condition
Module 18 – Loops in VBA
Module 19 – Debugging in VBA
Module 20 – Dashboard Visualization
Module 21 – Principles of Charting
Module 22 – Getting started with Pivot Tables
Module 23 – Statistics with Excel
24 Hours 9 Module
PreviewModule 01 – Introduction to NoSQL and MongoDB
Module 02 – MongoDB Installation
Module 03 – Importance of NoSQL
Module 04 – CRUD Operations
Module 05 – Data Modeling and Schema Design
Module 06 – Data Management and Administration
Module 07 – Data Indexing and Aggregation
Module 08 – MongoDB Security
Module 09 – Working with Unstructured Data
16 Hours 13 Module
PreviewModule 01 – Introduction to SQL
Module 02 – Database Normalization and Entity Relationship Model
Module 03 – SQL Operators
Module 04 – Working with SQL: Join, Tables, and Variables
Module 05 – Deep Dive into SQL Functions
Module 06 – Working with Subqueries
Module 07 – SQL Views, Functions, and Stored Procedures
Module 08 – Deep Dive into User-defined Functions
Module 09 – SQL Optimization and Performance
Module 10 – Advanced Topics
Module 11 – Managing Database Concurrency
Module 12 – Programming Databases Using Transact-SQL
Module 13 – Microsoft Courses: Study Material
Projects will be a part of your Data Science Architect Master’s program to consolidate your learning. It will ensure that you have real-world experience in Data Science.
This Data Scientist Master’s program in the USA is created and delivered to help you land top jobs in the world’s best organizations. The training includes real-world projects and case studies, after which you will receive industry-recognized certifications from Intellipaat.
This training program aims to prepare you for the following certification exams:
As per the study, Data Scientist is the best career in the 21st century
Harvard Business ReviewThe Big Data market size is predicted to go up to US$229.4 billion by 2025 worldwide
Markets and MarketsThe average salary of a Data Scientist is around US$120,160 per year
IndeedLand Your Dream Job Like Our Alumni
You can learn Data Science Master’s programs from Intellipaat whether you are sitting at home or in an office in Alabama, Arizona, Carolina, California, Florida, Georgia, Indiana, Kansas, Massachusetts, Michigan, New Jersey, New York, Ohio, Texas, Washington, or Virginia. The course is available in most areas of the US.
The master’s in data science program is extensively designed by industry experts to ensure that you master the data science domain and successfully complete the training. Whereas, individual courses are for those who want to focus on particular specializations. If you want to master the whole data science domain, then this master’s course is for you.
Intellipaat offers query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail yourself of email support for all your queries. We can also arrange one-on-one sessions with our support team If your query does not get resolved through email. However, 1:1 session support is given for 6 months from the start date of your course.
Intellipaat provides placement assistance to all learners who have completed the training and moved to the placement pool after clearing the PRT (Placement Readiness Test). More than 500+ top MNCs and startups hire Intellipaat learners. Our alumni work with Google, Microsoft, Amazon, Sony, Ericsson, TCS, Mu Sigma, etc.
No, our job assistance is aimed at helping you land your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final hiring decision will always be based on your performance in the interview and the requirements of the recruiter.
