• 48-49, 3rd floor, Jai Ambey Nagar, Opp. Jaipur Hospital, Tonk Rd, Jaipur
  • (+91) 8094336633
  • careers@zeetronnetworks.com

Data Science Training in Jaipur

  • Data Science

    Zeetron Network is one of the best Data Science training companies in Jaipur with experienced professionals and a dedicated team. Our data science training in Jaipur will cover the complete standard module of Data Science and related technical topics that is important for students and professionals to know to become a dedicated professional or data scientist for multiple companies. Zeetron Networks’ Data Science online and offline training in Jaipur includes the complete syllabus like Python, basics of R, Statistics, Internal Statistics, Regression, and ANOVA, etc.

    We will teach you those things in python which are important to learn in order to get recognition as an expert professional of python in the IT sector.

    Zeetron Network is the right place for data science certification training just because we are having Real-Time Expert Trainers, Certificate, Training & Project based internship in Data Science, affordable fee schedule, flexibility in services as well as complete placement assistance for students. We are the only data science internship company in Jaipur which is more focused on industrial learning and quality teaching to our students.

    The learning of Data Science will lead a person to groom his professional career into multiple related technologies like Machine Learning, Artificial Intelligence using Big Data Hadoop as a data scientist or data analyst in Jaipur

  • Data Science Learning Outcomes

    • Develop hard skills in Data Science like Python, R Programming, Statistics, Machine Learning, Artificial Intelligence, Tableau, Deep Learning, Neural Networks, TensorFlow, Unix, Git, SQL.
    • Our Courses integrate real-world hands-on training with case studies & projects using Datasets from companies like Amazon, Facebook, Adobe, Walmart, etc.
    • Work on Real Projects, Build a Portfolio, Attend Interviews and Get Hired.
    • Certified Data Science Trainer with Years Real Time Industry Experience.
    • Best faculty with excellent Lab Infrastructure along with detailed course material.
    • Prepare your CV/Resume to attend Interviews and securing a Job.
    • We Share Common Interview FAQs, Interview Handling Skills & Real-Time Case studies.
    • One-to-one Attention by Instructors
    • Start learning data science through the promising Julia language and to become an efficient data scientist

What is Data Science?

Data science refers to the study of where information comes from, what it means and how it can be turned into valuable information in the creation of corporate businesses and IT strategies.

Mining large amounts of structured, unstructured and semi-structured data to identify relations can help an organization limit its costs, increase efficiencies, identify new market opportunities and enlarge the organization's competitive advantage.

Today, Data Science is a much-talked subject and moreover, its significance is being deliberated among the business managers who are eager to hire a brilliant professional onboard their firm. Data Science is a growing field and the demand for data scientists has been anticipated to increase this decade in the IT sector.

Statistics

  • Introduction to Data Science
  • The need for Data Science
  • BigData and Data Science
  • Data Science and machine learning
  • Data Science Life Cycle
  • Data Science Platform
  • Data Science Use Cases
  • Skill Required for Data Science
  • Linear Algebra
  • Vectors
  • Matrices
  • Optimization
  • Theory Of optimization
  • Gradients Descent
  • Descriptive vs. Inferential Statistics
  • Types of data
  • Measures of central tendency and dispersion
  • Hypothesis & inferences
  • Hypothesis Testing
  • Confidence Interval
  • Central Limit Theorem
  • Probability Theory
  • Conditional Probability
  • Data Distribution
  • Binomial Distribution
  • Normal Distribution

 

Python for Data Science

  • Why Python, its Unique Feature and where to use it?
  • Python Environment Setup/shell
  • Installing Anaconda
  • Understanding the Jupyter notebook
  • Python Identifiers, Keywords
  • Discussion about installed modules and packages
  • Python Data Types and Variable
  • Condition and Loops in Python
  • Decorators
  • Python Modules & Packages
  • Python Files and Directories manipulations
  • Use various files and directory functions for OS operations
  • Built-in modules (Library Functions)
  • Numeric and Math’s Module
  • String/List/Dictionaries/Tuple
  • Complex Data structures in Python
  • Python built-in function
  • Python user-defined functions
  • Array Operations
  • Arrays Functions
  • Array Mathematics
  • Array Manipulation
  • Array I/O
  • Importing Files with Numpy
  • Data Frames
  • I/O
  • Selection in DFs
  • Retrieving in DFs
  • Applying Functions
  • Reshaping the DFs - Pivot
  • Combining DFs
  • Merge
  • Join
  • Data Alignment
  • Matrices Operations
  • Create matrices
  • Inverse, Transpose, Trace, Norms, Rank etc
  • Matrices Decomposition
  • Eigenvalues & vectors
  • Basics of Plotting
  • Plots Generation
  • Customization
  • Store Plots

 

Machine Learning

  • Data Exploration
  • Missing Value handling
  • Outliers Handling
  • Feature Engineering
  • Importance of Feature Selection in Machine Learning
  • Filter Methods
  • Wrapper Methods
  • Embedded Methods
  • Introduction to Machine Learning
  • Logistic Regression
  • Naïve Bays Algorithm
  • K-Nearest Neighbor Algorithm
  • Decision Trees (SingleTree)
  • Support Vector Machines
  • Model Ensemble
    • - Bagging
    • - Random Forest
    • - Boosting
    • -Gradient Boosted Trees
  • Model Evaluation and performance
    • - K-Fold Cross-Validation
    • - ROC, AUC, etc...
  • Simple Linear Regression
  • Multiple Linear Regression
  • Decision Tree and Random Forest Regression
  • Similarity Measures
  • Cluster Analysis and Similarity Measures
  • Principal means Clustering
  • HierarComponents Analysis
  • Association Rules Mining & Market Basket Analysis
  • Basics
  • Term Document Matrix
  • TF-IDF
  • Twitter Sentiment Analysis

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