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Data Science Training in Hyderabad

Course Duration: 90 Days

The Data Science Training course in Hyderabad is designed to accelerate your IT career. Crafted by expert Data Scientists, this course integrates theory, case studies, and practical projects to transform you into a proficient Data Science professional. Our Data Science Certification program in Hyderabad delivers hands-on training, equipping students with essential skills such as Python/R programming, Statistical Analysis, Unstructured Data Handling, Data Extraction, Data Cleansing, Raw Data Analysis, Data Modeling, Predictive Analysis, Data Science lifecycle management, Data Visualization, and more.
Beyond traditional classroom sessions, we also offer online Data Science certification training. Enroll in our top-notch Data Science with Python training program to earn your certification and excel in the field of Data Science.

Overview of the Data Science Training Course:

The Indian analytics industry is experiencing exponential growth, with IT enterprises and tech-based startups actively seeking skilled Data Scientists to drive economic growth. Experts predict that India will soon become a hub for data analytics jobs, with the market expected to reach $6 million by 2025. More than 300,000 new job opportunities arise annually in this domain. Hyderabad, being a hub for IT enterprises and startups, offers numerous job vacancies, making it an ideal location for pursuing a career in Data Science.
Data Science has emerged as one of the highest-paying skills in the IT industry, and the growing demand for skilled professionals makes enrolling in this course a wise choice. Our Data Science course in Hyderabad is designed according to industry standards and is suitable for individuals interested in learning about Data Science and its various stages. From foundational concepts to the complete Data Science lifecycle, this course covers all essential aspects.

Various industries such as IT, Healthcare, Pharmaceutical, E-commerce, Banking, Insurance, Media, and Retail have a significant demand for Data Scientists. The current surge in demand for Machine Learning and Data Science has led to lucrative career opportunities, with salary packages ranging from $143,500 to $180,500. CB HR Solutions Technologies’ Data Science classes in Hyderabad equip students with the latest tools, techniques, and algorithms, preparing them for high-paying job roles. Our Data Science Classroom Training in Hyderabad is an excellent choice for those committed to a successful career as a Data Scientist.

Real-Time Data Science Certification Training:

The demand for Data Science professionals is soaring, making it a lucrative career option for individuals from diverse backgrounds. Our Data Scientist Course in Hyderabad ensures that you stay on the right career path to achieve success in this field. Our institute provides the perfect platform to master core technical and non-technical skills associated with Data Science. Through hands-on experience in programming languages like Python for Data Science and popular libraries like Scikit-learn, you will gain the necessary expertise to handle large volumes of data.
Completing our Data Science Certification course earns you a course completion certificate, opening doors to high-salaried job opportunities in Data Science. As one of the best Data Science certification training institutes in Hyderabad, we cater to the high demand for skilled Data Science professionals. Enroll in our Data Science course today to embark on a rewarding career journey in the field of Data Science.
Completing our Data Science Certification course earns you a course completion certificate, opening doors to high-salaried job opportunities in Data Science. As one of the best Data Science certification training institutes in Hyderabad, we cater to the high demand for skilled Data Science professionals. Enroll in our Data Science course today to embark on a rewarding career journey in the field of Data Science.

Data Science Training in Hyderabad Curriculum

Introduction to Data Science

  • What is data science?
  • How is data science different from BI and Reporting?
  • What is difference between AI, Data Science, Machine Learning, Deep Learning
  • Job Land scape and Preparation Time
  • Who are data scientists?
  • What skillsets are required?
  • What is day to day job of Data Scientist
  • What kind of projects they work on?
  • End to End Data Science Project Life Cycle
  • Data Science roles – functions, pay across domains, experience

Business Statistics

  • Data types
  • Continuous variables
  • Ordinal Variables
  • Categorical variables
  • Time Series
  • Miscellaneous
  • Common Data Science Terminology
  • Descriptive statistics
  • Basics concepts of probability
  • Frequentist versus Bayesian Probability
  • Axioms of probability theory,
  • Permutations and combinations

Introduction to R

  • A Primer to R programming
  • What is R? Similarities to OOP and SQL
  • Types of objects in R – lists, matrices, arrays, data.frames etc
  • Creating new variables or updating existing variables
  • If statements and conditional loops – For, while etc.
  • String manipulations

Python for Data Science

  • Understanding the reason of Python’s popularity
  • Basics of Python: Operations, loops, functions, dictionaries
  • Numpy – creating arrays, reading, writing, manipulation techniques
  • Ground-up for Deep-Learning

Exploratory Data Analysis with Python

  • Getting to understand structure of Matplotlib
  • Configuring grid, ticks.
  • text, color map, markers, widths with Matplotlib
  • configuring axes, grid,
  • hist, scatterplots
  • bar charts
  • multiple plots
  • 3D plots

Data Munging with Python

  • Introduction to pandas
  • Data loading with Pandas
  • Data types with python
  • Descriptive Statistics with Pandas
  • Quartile analysis with Pandas
  • Sort, Merge, join with Pandas
  • Indexing and Slicing with pandas

Introduction to Artificial Intelligence

  • Dealing Prediction problem
  • Forecasting for industry
  • Optimization in logistics
  • Segmentation in customer analytics
  • Supervised learning

Artificial Intelligence I – Statistical Modelling

  • Linear Regression
  • Assumptions
  • Model development and interpretation
  • Sum of least squares

Artificial Intelligence II – Machine Learning

  • Supervised Learning
  • Decision trees and Random Forest
  • Classification and Regression trees(CART)
  • Process of tree building
  • Entropy and Gini Index
  • Problem of over fitting
  • Pruning a tree back
  • Trees for Prediction (Linear) – example

Artificial Intelligence III – Natural Language Processing

  • NLP I – Text Preprocessing
  • Tokenization
  • Stemming
  • Lemmatization
  • NLP II – Text Modelling

Artificial Intelligence IV – Deep Learning

  • ReLU
  • Sigmoid, Depth vs Width tradeoffs
  • Convolutional networks
  • Concepts of filters
  • Sliding

Practical use cases of AI and best practices in AI

  • Business problem to an analytical problem
  • Guidelines in model development

Big Data, Azure for AI, Data Science applications

  • Big data and analytics?
  • Leverage Big data platforms for Data Science
  • Introduction to evolving tools
  • Machine learning with Spark

Analytical Visualisation with Tableau

  • Why is it important for Data-Analyst
  • Tableau workbook walkthrough
  • Instruction of creation of your own workbooks
  • Demo of few more workbooks