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Innovision Learning accelerates your career in Data Science Master Program with by learning statistical concepts and data analysis techniques simultaneously.

If you are Project Manager, Program Manager, Business Analyst, and Test Manager. Theses course will propel you forward in your career. Are you ready to take the first step towards your Robotic Process Automation (RPA) and Artificial intelligence (AI) journey to help you set up your goal? Get trained in Data Sciences Master Program by our Industry Expert and highly experienced Trainers with Real-time Industry Projects at very low cost.

Enroll now and Safeguard yourself from Recession, Job losses and Salary Cuts. Transition your career into Emerging Technologies!

What is Data Science?

Data science is an interdisciplinary field focused on extracting knowledge from data sets, which are typically large. The field encompasses analysis, preparing data for analysis, and presenting findings to inform high-level decisions in an organization. As such, it incorporates skills from computer science, mathematics, statistics, information visualization, graphic design, and business Statistician Nathan Yau, drawing on Ben Fry, also links data science to human-computer interaction: users should be able to intuitively control and explore data. In 2015, the American Statistical Association identified database management, statistics and machine learning, and distributed and parallel systems as the three emerging foundational professional communities.

Opportunities for data scientists-one of today's hottest jobs-are rapidly growing in response to the exponential amounts of data being captured and analyzed. In the competitive working landscape, which sees an endless flow of information and communication, data scientists help major decision makers shift from ad hoc analysis to an ongoing conversation with data.

Future of Data Science and Data Scientist
  • For the needs of the future, it will spark the emergence of new data science paradigms. We can use more data to drive key business decisions. We will enable innovations like “Deep Learning”. It allows for accurate predictions and decision making.
  • “Data scientist is a broad catch-all title. ... “The future data scientist can therefore be even more specialized, tackling the most business-critical and complex challenges that will help their businesses make revolutionary leaps forward,” she concludes.
  • The purpose of Data Scientists is to extract, pre-process and analyze data. Through this, companies can make better decisions. Various companies have their own requirements and use data accordingly. In the end, the goal of Data Scientist to make businesses grow better.
  • Data science provides meaningful information based on large amounts of complex data or big data. Data science, or data-driven science, combines different fields of work in statistics and computation to interpret data for decision-making purposes.
  • Data Science as a multi-disciplinary subject encompasses the use of mathematics, statistics, and computer science to study and evaluate data. The key objective of Data Science is to extract valuable information for use in strategic decision making, product development, trend analysis, and forecasting.
  • Data Science training empowers professionals with data management technologies such as Hadoop, Flume, Machine learning, etc. If a candidate has the knowledge and proficiency of these significant data skills, it would be an added advantage for them to have an improved and competitive career.
Specializations and Associated Careers
  • Machine Learning Scientist: Machine learning scientists research new methods of data analysis and create algorithms.
  • Data Analyst: Data analysts utilize large data sets to gather information that meets their company’s needs.
  • Data Consultant: Data consultants work with businesses to determine the best usage of the information yielded from data analysis.
  • Data Architect: Data architects build data solutions that are optimized for performance and design applications.
  • Applications Architect: Applications architects track how applications are used throughout a business and how they interact with users and other applications.
Benefits SAFe Agilist Certification
  • Big data is very quickly becoming a vital tool for businesses and companies of all sizes.
  • The availability and interpretation of big data has altered the business models of old industries and enabled the creation of new ones.
  • Data-driven businesses are worth $1.2 trillion collectively in 2020, an increase from $333 billion in the year 2015.
  • Data scientists are responsible for breaking down big data into usable information and creating software and algorithms that help companies and organizations determine optimal operations.
  • As big data continues to have a major impact on the world, data science does as well due to the close relationship between the two.
Technologies and Techniques

There are a variety of different technologies and techniques that are used for data science which depend on the application.

Techniques

  • Clustering is a technique used to group data together.
  • Dimensionality reduction is used to reduce the complexity of data computation so that it can be performed more quickly.
  • Machine learning is a technique used to perform tasks by inference patterns from data.

Technologies

  • Python is a programming language with simple syntax that is commonly used for data science. There are a number of python libraries that are used in data science including numpy, pandas, and scipy.
  • R is a programming language that was designed for statisticians and data mining and is optimized for computation.
  • Tensorflow is a framework for creating machine learning models developed by Google.
  • Pytorch is another framework for machine learning developed by Face book.
  • Jupyter Notebook is an interactive web interface for Python that allows faster experimentation.
  • Tableau makes a variety of software that is used for data visualization.
  • Apache Hadoop is a software framework that is used to process data over large distributed systems.
What are prerequisites for enrollment?

There are no prerequisites for enrollment to the Masters Program. Whether you are an experienced professional working in the IT industry, or an aspirant planning to enter the world of Data Scientist, Masters Program is designed and developed to accommodate various professional backgrounds.

Why Data Science Master Program?

The Masters Program is a structured learning path recommended by leading industry experts and ensures that you transform into a Data Scientist. This immersive Data Scientist program starts with Data Science training to master important Data Extraction, Exploration Techniques, and Machine Learning Algorithms, then helps you gain expertise on Python for dealing with Big Data, followed by becoming adept at Apache Spark and it's machine learning capabilities and become proficient in trending skills about AI & Deep learning using Tensorflow and finally ends at Data Visualization using Tableau.

Individual courses at Innovision Learning focus on specialization in one or two specific skills, however if you intend to become a Data Scientist, then this is the path for you to follow. Data Science Masters Program makes you proficient in tools and systems used by Data Science Professionals. The curriculum has been determined by extensive research across the globe.

What are prerequisites for enrollment?

There are no prerequisites for enrollment to the Masters Program. Whether you are an experienced professional working in the IT industry, or an aspirant planning to enter the world of Data Scientist, Masters Program is designed and developed to accommodate various professional backgrounds.

Data Science Master Program Syllabus

Python Statistics for Data Science Course SELF PACED

Python Scripting allows programmers to build applications easily and rapidly. This course is an introduction to Python scripting, which focuses on the concepts of Python, it will help you to perform operations on variable types using Pycharm. You will learn the importance of Python in real time environment and will be able to develop applications based on the Object Oriented Programming concept. End of this course, you will be able to develop networking applications with suitable GUI.

Python Statistics for Data Science Course Curriculum

  • Understanding the Data
  • Probability and its uses
  • Statistical Inference
  • Testing the Data
  • Data Clustering
  • Regression Modeling
R Statistics for Data Science Course SELF PACED

AI & Deep learning with Tensorflow course will make you an expert in training and optimizing basic and convolution neural networks using real time projects and assignments. You will also master the concepts such as SoftMax function, Autoencoder Neural Networks, Restricted Boltzmann Machine (RBM).

R Statistics for Data Science Course Curriculum

  • Understanding the Data
  • Probability and its uses
  • Statistical Inference
  • Testing the Data
  • Data Clustering
  • Regression Modeling
Data Science Certification Course using R LIVE CLASS

Data Science Training lets you gain expertise in Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes using R. Data Science Training encompasses a conceptual understanding of Statistics, Time Series, Text Mining and an introduction to Deep Learning. Throughout this Data Science Course, you will implement real-life use-cases on Media, Healthcare, Social Media, Aviation and HR.

Data Science Certification Course using R Curriculum

  • Introduction to Data Science
  • Statistical Inference
  • Data Extraction, Wrangling and Exploration
  • Introduction to Machine Learning
  • Classification Techniques
  • Unsupervised Learning
  • Recommender Engines
  • Text Mining
  • Time Series
  • Deep Learning
Python Certification Training for Data Science LIVE CLASS

Data Science using Python programming certification course enables you to learn data science concepts from scratch. This Python Course will also help you master important Python programming concepts such as data operations, file operations, object-oriented programming and various Python libraries such as Pandas, Numpy, Matplotlib which are essential for Data Science.

Python Certification Training for Data Science Curriculum

  • Introduction to Python
  • Sequences and File Operations
  • Deep Dive – Functions, OOPs, Modules, Errors and Exceptions
  • Introduction to NumPy, Pandas and Matplotlib
  • Data Manipulation
  • Introduction to Machine Learning with Python
  • Supervised Learning - I
  • Dimensionality Reduction
  • Supervised Learning - II
  • Unsupervised Learning
  • Association Rules Mining and Recommendation Systems
  • Reinforcement Learning
  • Time Series Analysis
  • Model Selection and Boosting
Apache Spark and Scala Certification Training LIVE CLASS

Apache Spark and Scala Certification Training is designed to prepare you for the Cloudera Hadoop and Spark Developer Certification Exam (CCA175). You will get an in-depth knowledge on Apache Spark and the Spark Ecosystem, which includes Spark RDD, Spark SQL, Spark MLlib and Spark Streaming. You will get comprehensive knowledge on Scala Programming language, HDFS, Sqoop, FLume, Spark GraphX and Messaging System such as Kafka.

Apache Spark and Scala Certification Training Curriculum

  • Introduction to Big Data Hadoop and Spark
  • Introduction to Scala for Apache Spark
  • Functional Programming and OOPs Concepts in Scala
  • Deep Dive into Apache Spark Framework
  • Playing with Spark RDDs
  • Data Frames and Spark SQL
  • Machine Learning using Spark MLlib
  • Deep Dive into Spark MLlib
  • Understanding Apache Kafka and Apache Flume
  • Apache Spark Streaming - Processing Multiple Batches
  • Apache Spark Streaming - Data Sources
  • In-class Project
  • Spark GraphX (Self-Paced)
AI & Deep Learning with Tensor Flow LIVE CLASS

Deep Learning in Tensor Flow with Python Certification Training is curated by industry professionals as per the industry requirements & demands. You will master the concepts such as SoftMax function, Autoencoder Neural Networks, Restricted Boltzmann Machine (RBM) and work with libraries like Keras & TFLearn. The course has been specially curated by industry experts with real-time case studies.

AI & Deep Learning with Tensor Flow Curriculum

  • Introduction to Deep Learning
  • Understanding Neural Networks with Tensorflow
  • Deep dive into Neural Networks with Tensorflow
  • Master Deep Networks
  • Convolutional Neural Networks (CNN)
  • Recurrent Neural Networks (RNN)
  • Restricted Boltzmann Machine (RBM) and Auto encoders
  • Keras API
  • TFLearn API
  • In-Class Project
Tableau Training & Certification LIVE CLASS

Tableau 10 Certification training is aligned with the Tableau Qualified Associate Level Examination. It will help you become proficient in transforming data into interactive and shareable dashboards. The curriculum covers extensive concepts including Data Blending, creation of Charts, Graphs and LOD expressions using different versions of Tableau such as Tableau Desktop, Tableau Public and Tableau Reader. The training will also cover integration of Tableau with R and Big Data.

Tableau Training & Certification Curriculum

  • Introduction to Data Visualization
  • Visual Analytics
  • Visual Analytics in depth I
  • Visual Analytics in depth II
  • Dashboard and Stories
  • Mapping
  • Calculation
  • LOD Problem Sets & Hands on
  • Charts
  • Integrating Tableau with R and Hadoop
1 Capstone Project:

A Capstone Project serves as a final project that consolidates your entire master’s program learning. This will require you to understand a business case and present a solution to solve all the problem statements mentioned in the project.

Course Delivery
  • 232 Hrs Instructor Led Training
  • 104 Hrs Self-paced Videos
  • 253 Hrs Project work & Exercises
  • Flexible Schedule
  • Lifetime Free Upgrade
  • 24 x 7 Lifetime Support & Access

We offer you the most updated, relevant and high value real-world projects as part of the training program.

This way you can implement the learning that you have acquired in a real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning and practical knowledge thus making you completely industry-ready. You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. Upon successful completion of the projects your Skills will be considered equal to six months of rigorous industry experience.

 
What is Innovision Learning Masters Program and how is it different from the individual courses offered by Innovision Learning?

Masters Program is a structured learning path recommended by leading industry experts and ensures that you transform into Data Scientist. This immersive Data Scientist program starts with Data Science training to master important Data Extraction, Exploration Techniques, and Machine Learning Algorithms, then helps you gain expertise on Python for dealing with Big Data, followed by becoming adept at Apache Spark and it's machine learning capabilities and become proficient in trending skills about AI & Deep learning using Tensorflow and finally ends at Data Visualization using Tableau. Individual courses at Innovision Learning focus on specialization in one or two specific skills, however if you intend to become a Data Scientist, then this is the path for you to follow.

Why should I enroll for Masters Program?

Data Scientist Masters Program has been curated after thorough research and recommendations from industry experts. It will help you master concepts of Data Management, Statistics, Machine Learning and Big Data together with hands-on experience of tools & systems used by Data Scientists including Data Visualizations using Tableau. Innovision Learning will be by your side throughout the learning journey.

What are the topics covered as a part of the curriculum?

Topics covered but not limited to will be : Machine Learning, K-Means Clustering, Decision Trees, Data Mining, Python Libraries, Statistics, Scala, Spark Streaming, RDDs, MLlib, Spark SQL, Random Forest, Naïve Bayes, Time Series, Text Mining, Web Scraping, PySpark, Python Scripting, Neural Networks, Keras, TFLearn, SoftMax, Autoencoder, Restricted Boltzmann Machine, LOD Expressions, Tableau Desktop, Tableau Public, Data Visualization, Integration with R, Probability, Bayesian Inference, Regression Modeling etc.

What are the prerequisites for enrollment?

There are no prerequisites for enrollment to the Masters Program. Whether you are an experienced professional working in the IT industry, or an aspirant planning to enter the world of Data Scientist, Masters Program is designed and developed to accommodate various professional backgrounds.

Are the courses Instructor Led, or Self Paced?

Innovision Learning’s Masters Program is a thoughtful compilation of Instructor -Led and Self Paced Courses, allowing the learners to be guided by industry experts, as well as learn skills at their own pace. In the Data Science Masters Program, Data Science Certification Course using R, Python Certification Training for Data Science, Apache Spark and Scala Certification Training, AI & Deep Learning with Tensorflow, Tableau Training & Certification are Instructor - led Online Courses. Python Statistics for Data Science Course, R Statistics for Data Science Course, SQL Essentials Training & Certification, R Programming Certification Training, Python Programming Certification Training, Scala Essentials, MongoDB® Training, and Certification are self-paced Courses.

How long will it take me to be a certified Data Science Professional?

The recommended duration to complete this program is 34 weeks; however, it is up to the individual to complete this program as per their own pace.

If I enroll today, when shall I get access to all the courses?

As soon as you enroll, all the 13 courses mentioned in the curriculum will be added to your account. Innovision Learning provides its learners with immediate and lifetime access to every course, which is a part of the Masters Program.

Is there a specific order in which I have to complete the courses?

No, we do not enforce order of course completion. Our Masters Program recommends the ideal path for becoming a Data Scientist, however, it is learner’s preference to complete the courses in any order they intend to.

What is the eligibility criterion for being certified as Data Scientist?

Certificate of Completion for Masters Program shall be awarded to you once you have completed the individual Certification projects of the following courses as well as the Capstone Project: Python Statistics for Data Science Course R Statistics for Data Science Course Data Science Certification Training Python Certification Training Apache Spark and Scala Certification Training AI & Deep Learning with Tensorflow Tableau Training & Certification To aid your learning journey, we have added following elective courses in the LMS: SQL Essentials Training and Certification R Programming Certification Training Python Programming Certification Training Scala Essentials MongoDB Certification Training Completion of the above elective courses is not mandatory for the Master's Program certification criteria.

Will I be receiving Certificates for individual courses as well?

Yes, we would be providing you with certificate of completion for every course that is a part of the learning pathway, once you have successfully submitted the final assessment and it has been verified by our subject matter experts.

Do I need to complete the Capstone Project to obtain my Master's Certificate?

Yes, in addition to the successful completion of all individual courses, you need to attempt and complete the capstone project to receive the certificate for Master’s Program.

What would be the Job Titles after completing the course?

Data Engineer, Data Scientist, Data & Analytics Manager, Principal Scientist.

Program Features
  • As per your convenience
  • Weekday or weekend; morning or evening. Multiple options for everyone.
Never miss a class
  • You can always switch to another batch, depending upon your availability.
  • Personal Learning Manager
  • A human, who is ridiculously committed to answer all your queries.
Lifetime Access
  • You'll have the keys to all our presentations, quizzes, installation guides. All for a lifetime!

Jobs requiring Data Science skills are paying an average of $114,000. Advertised data scientist and data engineering jobs pay an average of $105,000 and $117,000 respectively.

28 % Annual Growth in job opportunities for data scientists, data developers and data engineers, across the globe.

2.7 Million Career Opportunities estimated for Data Science and analytical roles in 2020.

 

 

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COURSE FEATURES

  • Lectures 26
  • Quizzes 0
  • Duration 60 Hours
  • Skill level Beginner
  • Language English
  • Students 23
  • Assessments Self