Data Science Course

Data Science with Python and R

Embark on a transformative Data Science journey in Kolkata. Master key concepts, tools, and techniques through practical training. Elevate your career with our cutting-edge curriculum. Enroll now to unleash the potential of data science in the vibrant city of Kolkata.

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24th November, 2024

11:00 AM IST

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Data Science Course in Kolkata

Looking to accelerate your career in Data Science Course in Kolkata? Look no further than Data Brio Academy’s Data Science certification program. Our program is designed and taught by experts who are defining world standards in the field.

In our data science course in Kolkata, you will gain hands-on experience in data exploration, data visualization using various tools like TableauMicrosoft PowerBI, SQL, and MS Excel. You will master statistical analysis, predictive analytics, NLP, and Machine Learning models (supervised and unsupervised) with a focus on model evaluation using R and Python languages.

Our course is designed to provide a comprehensive understanding of the complete data science project lifecycle through industry cases, capstone projects, and 1:1 project mentoring. You will gain practical, hands-on experience in each step of the project lifecycle, from data collection and cleaning to model building and evaluation.

With our Data Science Course, you will gain the skills and knowledge necessary to excel in your data science career in Kolkata. Our program is designed to prepare you for success in the rapidly growing field of data science and AI.

Join our Data Science Course Training in Kolkata today and take the first step towards a successful career in this exciting and dynamic field!

 

Why Data Brio Academy?

Who this course is for:

Eligibility

Training and Placement

Subsequent to the completion of our Data Science Certification course, assignments, projects, and placement assistance will kick start with resume building. Mock Interviews will be conducted for a better understanding of their interview readiness, one-to-one discussion on job description during interview calls, etc. This helps the participant to retrospect and understand their capability to improve the readiness. Participants can attend and successfully crack the interviews with complete confidence. Students Successfully Placed in Companies:

Accredition & Affiliation

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Data Science Course Curriculum

Duration – 120 Hours

Data Science Methods and Models 

  • Population and Sample
  • Elementary Probability, Correlation
  • Point & Interval Estimation
  • Hypothesis Testing, Type I & Type II Error, P-Value
  • Basics of Inferential analytics
  • Normality Test
  • 1- Sample and 2-Sample Tests
  • HOV, ANOVA, Moods Median Test, Chi-square test etc
  • Assignments with data sets
  • Linear Regression
  • Assumptions and Diagnostics
  • Interactions and indicator variables
  • Descriptive & predictive models
  • Logistic Regression
  • Clustering technique
  • Decision Tree
  • Case studies
  • Multivariate Analysis
  • Factor Analysis
  • Case studies
  • Time Series data
  • Methods – MA, Exponential Smoothening, ARIMA
  • Evaluating best forecasts
  • Generative AI (GenAI) – Large Language Models (LLM) and RAG
  • Image Cognition (Video, Image) 

R Programming for Data Science

  • The R console, and the command interpreter
  • R scripts and running R scripts
  • The RStudio GUI and R Packages
  • Getting help in R and R functions
  • Basic object – Vector & operations
  • Data structures – matrices, lists, arrays, data frames
  • Manipulating data structures
  • Reading and writing data from and to different file formats
  • The apply family of functions and its uses in efficient data processing
  • Basic string and date processing
  • Generating and using (pseudo) random samples
  • Basic R built-in functions
  • Recycling, Control flow, Recursion
  • Conditions, loops
  • Vectorization & vector Operation
  • Writing and using user-defined functions
  • Simple charts and graphs – histograms, scatter diagrams
  • Line plots, boxplots, pareto charts, etc.
  • Plot function
  • Descriptive statistics
  • Hypothesis tests and ANOVA
  • Linear Regression including interactions and indicator variables
  • Machine learning algorithms

Python Programming

  • Getting, installing & navigating the software
  • Anaconda IDE, Jupyter, Spider, Pycharm, Google colab
  • Statements and comments
  • Input, Output and Import
  • Python operators, variables
  • Python numbers, string
  • Python list, Tuple, String, Set, Dictionary etc.
  • Dataframes, Modules, Packages
  • Conversion between data types
  • Troubleshooting and error handling
  • Conditionals
  • Functions – new and built-in function
  • Flow Control – If – Else, For loop, while loop etc.
  • Break & control
  • Data Management, Visualization and Basic analytics using libraries – Pandas, Numpy, Scipy, Scikitlearn, Matplotlib, Seaborn, Plotly etc.
  • Descriptive statistics
  • Linear Regression including interactions and indicator variables
  • Machine learning algo in python – Classification & Regression, Decision Tree
  • Time-series forecasting

Analytics & Visualisation

  • What is analytics, data science, ML, AI?
  • Data – Different perspectives and types
  • Sources of Data – public data, business data
  • Structured and unstructured data
  • Central tendency, dispersion, cross tabulations
  • Association, covariance, correlation
  • Trend, seasonality, line chart
  • Histogram, boxplot, scatter plot, pareto chart etc.
  • Derived metrics & KPI
  • Using formula & data validation
  • Pivot table and charts, Conditional formatting
  • Lookups, error handling
  • Numerical and graphical summaries
  • PowerBI or Tableau workspace – dimensions & measures
  • Tables & charts, various data source connectivity
  • Filters – slicing & dicing of multi-dimensional data
  • GIS-based visualization, time-series data
  • Calculated fields, Interactive dashboards
  • Basics of RDBMS
  • Tables & queries (select queries – group by, order by, having etc.)
  • Keys & joins (left, right, inner, outer)
  • Python & Google colab
  • MS Excel or equivalent
  • Tableau / PowerBI
  • MySQL or equivalent
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Our Certificates

Gain Industry-Recognized Certificates in Data Science with Python and R

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Our Placements

Our certified professionals, mentored by experts and connected to top employers, are shaping the future of data science at leading MNCs.

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