Diploma in Data Science Course in San Antonio

Diploma in Data Science in San Antonio

Henry Harvin® No.1 Data Science Course by India Today

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  • 1.1 Million Learners
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  • 81% Report Career Benefits

Expedite your Career with Prestigious Diploma in Data Science | Learn Data Science with the #1 course and Get Ahead in Your Career | Learn Extensive use of Tools & Technologies and Analytics Techniques

Starts In 7 day

02 Dec 2024

Learning Period

288 Hours

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There's a reason that 95% of our alumni undertake 3+ courses as a minimum with Henry Harvin®

Know the complete offerings of our Diploma in Data Science in San Antonio

Key Highlights

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288 Hours of Instructor-Led Sessions
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96 Hours of Live Interactive Doubt Solving Sessions
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48 Hours of Live Master Sessions by Industry Experts
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384 Hours of Self-Paced Learning
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384 Hours Hands on with Cloud Labs
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Job-Ready Portfolio of 29 Capstone Projects
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78 Auto-Graded Assessments
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58+ Industry Case Studies
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432 Guided Hands-On Exercises
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29+ Assignments and Mini Projects
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3 Mock Interviews and 3 Hackathons
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Get 24 Months Gold Membership of Henry Harvin® Data Science & Analytics Academy
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Get a guaranteed Internship with Henry Harvin® and in top MNCs like J.P. Morgan, Accenture & many more via Forage
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Get 3 in 1 Placement support through Placement Drives, Premium access to Job portal & Personalized Job Consulting
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13 Hours of Mentorship by Industry Experts
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Earn Certification of Course from Henry Harvin®, Govt of India recognized & Award-Winning Institute and NSDC Certification

Our Placement Stats

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Average salary hike

2100+

Access the best jobs in industry

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Maximum salary hike

Access the best jobs in the industry

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You Get 10-In-1 Program

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.

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Guaranteed Internship

Get a guaranteed Internship with Henry Harvin® and in top MNCs like J.P. Morgan, Accenture & many more via Forage.

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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

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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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About Diploma in Data Science in San Antonio

Why Data Science?

According to a recent evaluation, more than 93% of the firms use Artificial Intelligence for enhanced products and services

  • 43% of Professionals in Business Analytics in India have work experience of 3 years
  • 67% of Jobs are open for fresher or professionals with experience of less than 5 years
  • It is estimated, that by 2022, jobs in  Data Science and analytics arena will have a void of 2.9+ Million jobs   
  • The Data Science Industry is estimated to be growing at a remarkable rate of 33.7% CAGR (Compound Annual Growth Rate)
  •  It is estimated that India will become one of the Top 5 Leading Markets in Big Data by the end of 2021

“Big Data is at the Foundation of all Mega Trends that are happening”   - Chris Lynch 

Agota™ Framework

It is a versatile 10-in-1 program that includes various aspects of competency development and career development.

  • Training: 288 hours of Two-Way Live Online Interactive Sessions
  • Projects: Facility to undergo projects in artificial intelligence, tableau & more
  • Masterclass: Access to 52+ Masterclass Sessions for essential soft skill development
  • Student Engagement & Events: Free Access to #AskHenry Hackathons and Competitions & many other facilities from Henry Harvin®
  • Membership: Get 24 Months Gold Membership of Henry Harvin® Data Science & Analytics Academy for the Diploma in Data Science course 
  • E-Learning  Free access to 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.
  • Certification: Get course completion Certification of Diploma in Data Science from Henry Harvin® Govt. of India recognized Award - Wining Institute & NSDC to showcase expertise.
  • Internship Support: Get a guaranteed Internship with Henry Harvin® and in top MNCs like J.P. Morgan, Accenture & many more via Forage.
  • Entrepreneurship Mentorship: Mentorship from Young Successful Entrepreneurs to set up a sustainable & scalable Business from scratch at both Freelance and entrepreneur levels
  • Placement Support: Get 3 in 1 Placement support through Placement Drives, Premium access to Job portal & Personalized Job Consulting

Trainers at Henry Harvin®

  • Most respected industry experts with 15+ years of working experience and recognized by numerous organizations over the years for their work
  • They have delivered 450+ keynote classes for the Diploma in Data Science
  • Have delivered 500+ lectures and are currently empaneled as domain experts with Henry Harvin® Data Science & Analytics Academy

Gold Membership Benefits

  • Avail 24 Months Gold Membership of Henry Harvin® Data Science & Analytics Academy that includes E-Learning Access through recorded Videos, Games, Projects, CPDSPe Studies
  • Access to Masterclass Sessions
  • Earn the Prestigious Henry Harvin®️ Alumni Status and become one of the reputed 4,60,000+ Alumni across the globe.
  • Guaranteed Internship with Henry Harvin®️ or partner firms
  • Weekly 10+ job opportunities offered.
  • Experience Industry Projects during the classes

Alumni Status

Become a part of the Elite Data Science & Analytics Academy of Henry Harvin® and join the 4,60,000+ large Alumni Network Worldwide.

Learning Benefits Of Data Science

  • Be well accomplished  in analytics tools and technologies such as Python, Tableau, SQL
  •  Know about the Machine learning techniques such as Regression, Predictive Clustering, Time Series Forecasting, Classification, etc.
  • Create an analytics framework using statistics and data modeling to structure any Business problem 
  • Learn to use  data cleaning and data transformation operations using tools and Techniques
  •  Learn Comprehensively about  Deep Learning, Natural Language Processing (NLP)
  •  Be Job-ready for the post of Data Scientist, Data Engineer, or Analyst for top Analytics companies  

 

 

Recognitions of Henry Harvin® Education

  • Winner of Top Corporate Training Award, Game-Based Learning Company of the Year under 40 Business World Award 
  • Affiliated with American Association of EFL, Ministry of Corporate Affairs, MSME, UKAF, UKCert, Project Management Institute (PMI), and ISO 29990:2010 certified. 
  • Reviews: 1400+ Google Reviews, 200+ Youtube Testimonials with 4.5+ Rating. Rate on Goabroad, Trustpilot, Gooverseas & more

 

 

Career Benefits

       

  • Become Eligible for Jobs in Data Science demanding background
  • Open doors to Job Opportunities Abroad demanding specialization
  • Get Promoted in current profile with most in-demand skill
  • Distinguish your profile from peers during Job Interviews
  • Improve CV & LinkedIn Profile with professional development

 

Know the complete offerings of our Diploma in Data Science in San Antonio

Curriculum For Diploma in Data Science in San Antonio

  • icons-carri33Live Course 1: Programming for Non Programmers

    Programming is an increasingly important skill. This course will establish your proficiency in handling basic programming concepts. This program will help you to gain basic programming concepts like data types, variables, strings, loops, functions, and software engineering concepts like multithreading and multitasking.

    Duration: 8 hours

    Key Learning Objectives

    - Achieve fundamental programming knowledge

    Understanding the basics of data structures, data types, variables, C++, and JAVA

    Course Curriculum

    - Course Introduction

    - Java Foundation

    - C++ Foundation

    - Jira 

  • icons-carri33Live Course 2: Statistics for Data Science

    Statistics is the discipline of allocating a prospect through the classification, collection, and analysis of data. A substructure part of Data Science, this Course helps you in defining the statistical terms. The Course explains measures of central tendency and dispersion and comprehended skewness, correlation, regression, and distribution. It will enable you to make data-driven predictions through statistics and the essential applications of it.

    Duration: 8 hours

    Key Learning Objectives 

    - Learn the fundamentals of statistics

    - Collaborate with different types of data

    - How to organize different types of data

    - Compute the measures of central tendency, asymmetry, and variability

    - Evaluate correlation and covariance

    - Distinguish different types of distribution and work on it

    - Estimate confidence intervals

    - Perform and Evaluate hypothesis testing

    - Make data-driven decisions

    - Know comprehensively  the mechanics of regression analysis

    - Carry out regression analysis

    - Use and understand dummy variables

     

    Course curriculum 

     

    Lesson 1 - Introduction 

    Lesson 2 - Sample or Population Data? 

    Lesson 3 - The Fundamentals of Descriptive Statistics 

    Lesson 4 - Measures of Central Tendency, Asymmetry, and Variability 

    Lesson 5 - Practical Example: Descriptive Statistics 

    Lesson 6 - Distributions 

    Lesson 7 - Estimators and Estimates 

    Lesson 8 - Confidence Intervals: Advanced Topics 

    Lesson 9 - Practical Example: Inferential Statistics 

    Lesson 10 - Hypothesis Testing: Introduction 

    Lesson 11 - Hypothesis Testing: Let’s Start Testing! 

    Lesson 12 - Practical Example: Hypothesis Testing 

    Lesson 13 - The Fundamentals of Regression Analysis 

    Lesson 14 - Subtleties of Regression Analysis 

    Lesson 15 - Assumptions for Linear Regression Analysis 

    Lesson 16 - Dealing with Categorical Data

    Lesson 17 - Practical Example: Regression Analysis

     

     

     

     

     

  • icons-carri33Live Course 3: Data Science with R

    The next step to becoming a data scientist is learning R—the most in-demand open source technology. R is the most powerful Data Science and analytics language, which has a steep learning curve and vigorous community. Data Science with R is becoming the technology of choice for organizations that are adopting the power of analytics for competitive expedience.

    Duration: 32 Hours

    Key Learning Objectives 

    - Gain a substantial understanding of business analytics

    - Install R, R-studio, and workspace setup, and learn about the various R packages

    - Master R programming and understand how various statements are executed in R

    - Gain an in-depth understanding of data structure used in R and learn to import/export data in R

    - Define, understand and use the various apply functions and dplyr functions

    - Understand and use the various graphics in R for data visualization

    - Gain a basic understanding of various statistical concepts

    - Understand and use the hypothesis testing method to drive business decisions

    - Understand and use linear, non-linear regression models, and classification techniques for data analysis

    - Learn and use the various association rules and Apriori algorithm Learn and use clustering methods including K-means, DBSCAN, and hierarchical

    clustering

    Course curriculum

    Lesson 1 - R Basics 

    Lesson 2 - Data Structures in R 

    Lesson 3 - R Programming Fundamentals 

    Lesson 4 - Working with Data in R 

    Lesson 5 - Handling Data in R 

    Lesson 6 - Introduction to Business Analytics 

    Lesson 7 - Introduction to R Programming 

    Lesson 8- Data Structures 

    Lesson 9 - Data Management in R

    Lesson 10 - Advanced Data Visualization

    Lesson 11 - Descriptive Statistics in R

    Lesson 12 - Regression Analysis 

    Lesson 13 - Decision Tree: Classification 

    Lesson 14 - Clustering: K-means and Hierarchical

    Lesson 15 - Association Rule Analysis

  • icons-carri33Course 4: Data Science with Python

    This Data Science with Python course will set up your mastery of Data Science and analytics techniques using Python. In this Python for Data Science course, you will learn the essential concepts of Python programming and gain in-depth knowledge in data analytics, Machine Learning, data visualization, web scraping, and natural language processing

    Duration: 40 hours

    Key Learning Objectives 

    - Learn an in-depth understanding of Data Science processes, data wrangling, data exploration, data

       visualization, hypothesis building, and testing Install the required   

    - Understand Python environment and other auxiliary tools and libraries

    -  Understand the essential concepts of Python programming such as data types, tuples, lists, dicts,

       basic operators, and functions   

    - Perform high-level mathematical computing using the NumPy package and its vast library of

        mathematical functions 

    - Carry out scientific and technical computing using the SciPy package and its sub-packages such  

        as Integrate, Optimize, Statistics, IO, and Weave      

    -   Carry out data analysis and manipulation using data structures and tools provided in the Pandas

        package 

    -   Gain an in-depth understanding of supervised learning and unsupervised learning models such as  

       linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline

    -   Use the Matplotlib library of Python for data visualization

    -   Extract useful data from websites by performing web scraping using Python

     

    Course curriculum 

    Lesson 1 - Python Basics

    Lesson 2 - Python Data Structures

    Lesson 3 - Python Programming Fundamentals

    Lesson 4 - Working with Data in Python

    Lesson 5 - Working with NumPy Arrays

    Lesson 6 - Data Science Overview

    Lesson 7 - Data Analytics Overview

    Lesson 8 - Statistical Analysis and Business Applications

    Lesson 9 - Python Environment Setup and Essentials

    Lesson 10 - Mathematical Computing with Python (NumPy)

    Lesson 11 - Scientific Computing with Python (Scipy)

    Lesson 12- Data Manipulation with Pandas

    Lesson 13 - Data Visualization in Python using Matplotlib

  • icons-carri33Course 5: Natural Language Processing

    This Natural Language Processing course will give you a comprehensive detail of the science behind applying Machine Learning algorithms to process large amounts of natural language data. Learn the concepts of statistical machine translation and neural models, deep semantic similarity model (DSSM), neural knowledge base embedding, deep reinforcement learning technique, neural models applied in image captioning, and visual question answering using Python’s Natural Language Toolkit (NLTK).

    Duration: 16 hours

    Key Learning Objectives

    - Apply Deep Learning models to solve machine translation and conversation problems

    - Implement deep structured semantic models (DSSM) to retrieve information

    - Understand deep reinforcement learning techniques applied in Natural Language Processing

    - Use neural models applied in image captioning and visual question answering

    Course curriculum 

    Lesson 1 - Introduction to Natural Language Processing

    Lesson 2 - Feature Engineering on Text Data

    Lesson 3 - Natural Language Understanding Techniques

    Lesson 4 - Natural Language Generation

    Lesson 5 - Natural Language Processing Libraries

    Lesson 6 - Natural Language Processing with Machine Learning and Deep Learning

    Lesson 7 - Speech Recognition Technique

  • icons-carri33Course 6: Tableau

    This Tableau training will help you master the various aspects of the program and gain skills such as building visualization, organizing data, and designing dashboards. You will also learn concepts of statistics, mapping, and data connection. Tableau is an essential asset to those wishing to succeed in Data Science.

    Duration: 32 hours

    Key Learning Objectives 

    - Learn the concepts of Tableau, become proficient with statistics, and build interactive dashboards

    - Master data sources and datable blending, create data extracts, and organize and format data

    - Master arithmetic, logic, table and LOD calculations, and ad-hoc analytics

    - Become an expert on visualization techniques such as heat map, treemap, waterfall, Pareto, Gantt chart, and market basket analysis

    - Learn to analyze data using Tableau Desktop as well as clustering and forecasting techniques

    - Gain command of mapping concepts such as custom geocoding and radial selections

    - Master Special Field Types and Tableau Generated Fields and the process of creating and using parameters

    - Learn how to build interactive dashboards, and story interfaces and how to share your work

     

    Course Curriculum

    Lesson 1 - Getting Started with Data Visualization and Tableau

    Lesson 2 - Working with Tableau

    Lesson 3 - Working on Metadata and Data Blending

    Lesson 4 - Deep Diving with Data and Connections

    Lesson 5 - Creating Charts

    Lesson 6 - Adding Calculations to your Workbook

    Lesson 7 - Mapping Data in Tableau

    Lesson 8 - Dashboards and Stories

    Lesson 9 - Visualizations for an Audience

    Lesson 10- Integration of Tableau with R and Hadoop

     

     

  • icons-carri33Course 7: Simulated Data Science Projects

    • Retail
    • E-commerce
    • Web & Social Media
    • Banking
    • Supply Chain
    • Healthcare
    • Insurance
    • Entrepreneurship /Start-Ups
    • Finance & Accounts

  • icons-carri33Electives 1: Artificial Intelligence

    Module 1: Neural Network

    This module will equip the candidate with the knowledge of Nural Networks. Gain Comprehensive knowledge about the Activation Functions and feedforward neural network. Learn about backpropagation and gradient descent. Know about the full connected layer forward and backward pass. Get acquainted with Data Preprocessing, Data Augmentation, weight initialization, working with google collab, and more

    Module 2: Computer Vision

    This module will help the candidate to gain knowledge of Computer Vision. Learn to work with images. Gain knowledge about Convolutions 2D for images. Know about the CNN architectures. Get acquainted with the knowledge of Semantic segmentation using UNet, and more

    Module 3: Natural Language Programming (NLP)

    This module will equip the candidate with the knowledge of Natural Language Processing. Learn the Preprocessing in NLP-Tokenization, Lemmatization, Stemming, Normalisation, Stop words, BOW, TF-IDF. Know about Word embedding, POS Tagging, LSTM application, Encoder-Decoder attention, and more

  • icons-carri33Electives 2: Machine Learning

    The Machine Learning course will make you a Master in Machine Learning, a form of Artificial Intelligence that automates data analysis to enable computers to learn and adapt through experience to do specific tasks without explicit programming. You will learn concepts and techniques, including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms and prepare you for your role with advanced Machine Learning knowledge.

    Key Learning Objectives

    - Master the concepts of supervised and unsupervised learning, recommendation engine, and time series modeling

    - Acquire practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach that includes working on four

    major end-to-end projects and 25+ hands-on exercises

    - Acquire thorough knowledge of the statistical and heuristic aspects of Machine Learning

    - Implement models such as support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-n

    means clustering, and more in Python

    - Validate Machine Learning models and decode various accuracy metrics. Improve the final models using another set of optimization algorithms, which

    include Boosting & Bagging techniques

    - Comprehend the theoretical concepts and how they relate to the practical aspects of Machine Learning

    - Gain expertise in Machine Learning using the Scikit-Learn package

    - Use the Scikit-Learn package for natural language processing

  • icons-carri33Electives 3: Deep Learning with KERA & Tensorflow

    Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides.

Know the complete offerings of our Diploma in Data Science

Admission Closes On 02 Dec 2024

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Skills Covered

Descriptive Statistics

Model building and Fine Tuning

Explanatory Data Analysis

Supervised and Unsupervised Learning

Inferential Statistics

Machine Learning

Deep Learning

Neural Networking

Hypothesis Testing

Tools Covered

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Certifications

Get Ahead with Henry Harvin® Diploma in Data Science in San Antonio Certification

What you'll Learn in this course

Python Programming Fundamentals

SQL Manipulation

Working with NumPy Arrays

Project Management Methodologies

Data Cleaning Techniques

Hypothesis Testing

Our courses and Course Certificates are trusted by these industry leaders

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Career Services By Henry Harvin®

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We are dedicated to supporting our students throughout their career journey. Join us, and let's embark on a journey towards a successful and fulfilling career together.

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Exclusive access to our dedicated job portal and apply for jobs. More than 2100+ hiring partners’ including top start–ups and product companies hiring our learners. Mentored support on job search and relevant jobs for your career growth.

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Henry Harvin®️ ranks amongst the Top 500 Global Edtech Companies with 4,60,000+ Alumni, 900+ B2B Clients, 500+ Award Winning Trainers, and 1200+ Courses.

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Why Henry Harvin for the best Diploma in Data Science

Certified & Experienced Instructors

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