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Register in October and get 3 months of membership, absolutely free!
Henry Harvin® Ranks #1 for Data Science Courses by India Today
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Gain technical, analytical, and practical skills to solve real-world, data-driven problems | Work on real-time projects in Data Science with R, Hadoop Dev, Admin, Test and Analysis, Apache Spark, Scala, Deep Learning, Power BI, SQL, & more | Explore, analyze, manage & visualize large data sets using the latest technologies | Get trained from top notch Industry Professionals & uplift your career in the field of Data Science.
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There's a reason that 95% of our alumni undertake 3+ courses as a minimum with Henry Harvin®
The Data Science Course provides an understanding of data science methods in predictive modeling, data mining, machine learning, artificial intelligence, data visualization, python environment setup, installation of Tableau, and more. Explore advanced data science methodologies, the application of data science in specific industries, and cutting-edge technologies such as artificial intelligence and robotics. Work on various projects & get opportunities to apply these skills to a real-world problem.
Career Opportunities
It is a versatile 10-in-1 program that includes various aspects of competency development and career development.
Become a part of the Elite School of Data Science & Analytics of Henry Harvin® and join the 4,00,000+ large Alumni Network Worldwide
Open up a variety of career opportunities in data-driven industries
Grab highly valued roles related to data analysis, business intelligence, and machine learning
Fill the void of thousands of untapped data science positions in various sectors such as finance, healthcare, and technology
Secure competitive salaries and advancement opportunities in their chosen field
Get Promoted in current profile by showcasing advanced skills in data science
Stand out among other candidates with a Master's degree in Data Science, positioning oneself for leadership roles and increased responsibilities within their organization
Know the complete offerings of our Master’s Program in Data Science in Detroit
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Average salary hike
Access the best jobs in industry
Maximum salary hike
Two-way Live Training Course
Two-way Live Online Interactive Classroom Sessions
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Certification
Distinguish your profile with credentials and showcase expertise with our Hallmark Completion certificate
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Projects
Facility to undergo various projects along with the course.
Guaranteed Internship
Get a guaranteed Internship with Henry Harvin® and in top MNCs like J.P. Morgan, Accenture & many more via Forage.
Placement
Get 3 in 1 Placement support through Placement Drives, Premium access to Job portal & Personalized Job Consulting
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Student Engagement & Events
Free Access to #AskHenry Hackathons and Competitions & many other facilities from Henry Harvin®
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Masterclass
Access to 52+ Masterclass Sessions for essential soft skill development
Membership
Get Free Gold Membership of Henry Harvin®
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E-Learning Access
Free access to the E-learning Portal and future updates. Get access to PPTs, Projects, Quizzes, self-paced Video-based learning, a question bank, a library, practice tests, final assessment, a forum, and doubt sessions.
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Entrepreneurship Mentorship
Mentorship from Young Successful Entrepreneurs to set up a sustainable & scalable Business from scratch at both Freelance and entrepreneur levels
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Course 1: Python for Data Science
Module 1: Python Basics
In this module, the candidate will learn about Python Basics, which includes understanding Anaconda, IDEs, Git, and Creating and Managing Analytics
Module 2: Python Programming Fundamentals
In this module, the candidate will learn about Data Import and Export and Operators in Python.
Module 3: Python Data Structures
In this module the candidate will learn about the Data Structure of Python, which includes Basic Data Structures and Programming Constructs, Handling Libraries, Numpy, Pandas, and Matplotlib.
Module 4: Working with Data in Python
In this module the candidate will learn about Working with Data in Python, which includes Group Summaries, Managing Missing Values, Types of Joins, Merge, Partitioning Data into Train and Test Set, and Scaling of Data.
Module 5: Working with NumPy Arrays
In this module, the candidate will learn how to Work with NumPy Arrays, which includes an understanding of Attributes, Indexing, Slicing, Reshaping, Joining, and Splitting of Arrays.
Course 2: Data Science with Python
Module 1: Data Science Overview
In these data science classes, you will get an overview of data science, data mining, statistics, and more
Module 2: Data Analytics and Business Application
In this module learn about data analytics, tools and techniques in analytics, and more
Module 3: Python Environment Setup and Essentials
In this module, learn about python environment set up and essentials
Module 4: Mathematical Computing with Python
In this module, learn about mathematical computing with python
Module 5: Scientific Computing with Python
In this module, learn about scientific computing with python along with SciPy Library, managing and manipulating data
Module 6: Data Manipulation with Pandas
In this module, learn about data manipulation with pandas,group summaries, outliers detection, and more
Module 7: Data Visualization in Python using matplotlib
In this module learn about data visualization in python, graphs, plot parameters, and more
Course 3: Machine Learning
In these Data Science classes, we will cover the following
Module 1: Introduction to Analytics
Module 2: Analytical Modeling Overview
Module 3: Clustering & Decision Trees
Course 4: Tableau
In these Data Science classes, we will cover the following
Module 1: Introduction to Data Visualization and Power of Tableau
In this module the candidate will learn about Data Visualization, Comparison benefits against reading raw numbers, Real use cases from various business domains, Examples of using Tableau, installing Tableau, Tableau interface, Connecting to Data source, Tableau data types and Data preparation
What is data visualization?
Module 2: Architecture of Tableau
In this module the candidate will learn about Architecture of Tableau, which includes learning of the installation, Desktop Architecture and Interface of Tableau, how to start with Tableau and the ways to share and export the work done in Tableau. The candidate will also be provided with a few Hands-on exercises, which will enhance the understanding of the Tableau
Topics:
Hands-on Exercise:
Module 3: Working with Metadata and Data Blending
In this module the candidate will learn working with Metadata and Data Blending, which includes understanding Connection to Excel, Cubes and PDFs, Management of the Metadata, preparation of Data, Joins and Unions , and how to deal with NULL Values, Cross- database joining, data extraction etc. The candidate will also be provided with Hands-on Exercises which will enhance the understanding of the candidate, of the topic and its working
Topics:
Hands-on Exercise:
Module 4: Creation of Sets
In this module the candidate will learn about Creation Sets, in which you will learn how to Mark, Highlight, Sort, Group, and use Sets, understand what are Constant Sets, Computed Sets, Bins etc. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned
Topics:
Hands-on Exercise:
Module 5: Working with Filters
In this module the candidate will learn about Filters, how to work with Filters, Filtering Continuous Dates, Dimensions and Measures, create folders in Tableau, sorting in Tableau, Filtering in Tableau and the order of Operations, types of Sorting and Filters. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned
Topics:
Hands-on Exercise:
Module 6: Organizing Data and Visual Analytics
In this module the candidate will learn about Visual Analytics and Organizing Data, in which the candidate will learn about usage of Formatting Pane and how to Format Data using Labels and Tooltips, Edit Axes and annotations, K-means cluster analysis, Trend and Reference lines, Visual Analytics and Forecasting, Confidence Interval, Reference lines and Bands. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned and its working
Topics:
Hands-on Exercise:
Module 7: Working with Mapping Preview
In this module the candidate will learn about Mapping Preview, which includes Working on Coordinate points and the background image, Plotting Longitude and Latitude, editing unrecognized Location, Customizing Geocoding, Maps etc., Map visualization, Custom territories, Map box WMS map and creating Map projects in Tableau and Dual Axes Maps. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned and its working
Topics:
Hands-on Exercise:
Module 8: Working with Calculations and Expressions
In this module the candidate will learn about Calculations and functions in Tableau, LOD expressions, aggregation and Replication with LOD expressions, Nested LOD expressions, Levels of details, Quick table calculations, Creation of calculated fields and Predefined calculations and validation
Module 9: Working with Parameters Preview
In this module the candidate will learn about Parameters, creating and its calculations, using Parameters with calculations Column and chart selection parameters, usage of Parameters in filter sessions, calculated fields and in reference line. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned and its working
Topics:
Hands-on Exercise:
Module 10: Charts and Graphs
In this topic the candidate will learn about Charts and Graphs, such as, Dual axes graphs, Histograms, Single and dual axes, Box plot, Charts; motion, pie , bar etc., Maps: tree and heat maps, Market Based Analysis and text and highlighted table. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned and its working
Topics:
Hands-on Exercise:
Module 11: Dashboards and Stories
In this module the candidate will learn about Dashboard, which includes topics such as, building and formatting, best practices for making creative dashboard, creating stories, updating the story points, Adding annotations with descriptions, Highlight actions, URL actions, types of Joins, Tableau field types, Saving as well as publishing data source, difference between Live and Extract connection and various file types. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned and its working.
Topics:
Hands-on Exercise
Module 12: Tableau Prep
In this module the candidate will learn about Tableau prep, how Tableau prep helps combine join, sharp, and clean data for analysis, creation of smart examples with Tableau prep, and how data preparation is made simple and accessible, integrating Tableau prep with Tableau analytical workflow and a clear understanding the seamless process from data preparation to analysis with Tableau prep.
Module 13: Integration of Tableau with R and Hadoop
In this module the candidate will learn about Tableau with R and Hadoop, which includes Application and use cases of R, Deploying R on the Tableau platform, R functions in Tableau and The integration of Tableau with Hadoop. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned and its working
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Complementary Module 1: Soft Skills Development
Complimentary Module 2: Resume Writing
Resume Writing
Know the complete offerings of our Master’s Program in Data Science
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Data Import & Export
Data Visualization
Filtering & Sorting Data
Analytical Modeling
Statistics
Natural Language Processing
Creating & Managing Analytics
Building Graphs
Logistic Regression
Projects
Projects
Projects
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