Gen AI and LLM Course

Learn Data Science with Generative AI

Learn to utilize the power of Gen AI to drive innovation and solve complex data science problems with our comprehensive Generative AI Course in Kolkata. Our world-class instructors will guide you through Generative AI, RAG architecture, Prompt Engineering and AI applications in Computer Vision, Deep Learning, Image Cognition, Conversational Chatbot and Voice. Enroll now to get your dream job in AI !

Get in Touch

New Batch Starting:

22nd December, 2024

11:00 AM IST

Limited Seats

Data Science with Generative AI Course in Kolkata

Are you seeking an opportunity to build a successful career in Data Science and Generative AI? You’re at the right place! Our comprehensive Data Science with Gen AI program will equip you with the skills and knowledge you need to harness the power of AI in real-world applications.

Gain deep insight into Artificial Intelligence and how it can be used along with Data Science techniques in real-world to solve business problems. In this course, you’ll become a master in data exploration, manipulation, and visualization using different tools and techniques. You’ll also gain in-depth knowledge and technical expertise in Deep Learning and AI applications such as Generative AI, Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Prompt Engineering, and Image Cognition.


Our course is designed in such a way that you’ll become industry-ready after completion. We understand the importance of practical knowledge and therefore, we’ve focused on hands-on learning through real-world industry use cases and internships. You’ll not only learn theoretical concepts but also know practical applications.

Our faculty consists of world-class industry leaders as mentors who will guide you throughout your journey. This is the best Generative AI course as you not only learn the theory of LLMs, SLMs, RAG etc. but also work on practical industry problems during your internship using GenAI.

With the rapid growth of Data Science and AI applications, our course provides an opportunity to establish your career in this emerging field. Be a part of Data Brio Academy and dive into the future of AI with our Data Science and Generative AI course. Learn to harness the power of LLMs and AI copilots like GPT-4, Mistral, Claude, Gemini, Prompt Engineering and RAG to create innovative AI solutions.

 

Why Data Brio Academy?

Who this course is for:

Eligibility

Training and Placement

Subsequent to the completion of our Gen AI 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

iso logo 1
cii logo 1
nasscom new
dsf logo 1
FUTURESKILLS LOGO new

Data Science with Gen AI Course Curriculum

Duration – 120 Hours

Generative AI – 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, 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
  • What is Generative AI?
  • What is Deep Learning?
  • Definition and core concepts
  • How Generative AI differs from traditional AI
  • Generative AI (Gen AI) – Large Language Models (LLM)
  • RAG Architecture and Prompt Engineering
  • Different LLMs like GPT-4, Gemini, Claude 2, Llama 2 etc.
  • Image Cognition (Video, Image) – image segmentation and classification
  • Object detection and information extraction using Azure Computer Vision and Amazon Rekognition

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
  • Power BI 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, Jupyter Notebook, VS Code
  • MS Excel or equivalent
  • Tableau / PowerBI
  • MySQL or equivalent
  • Azure Computer Vision
  • GPT, Claude
  • Amazon AWS AI Services / Azure AI
course gal 1
course gal 2
course gal 4
course gal 5
Our Certificates

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

Machine Learning with Python 1

Our Placements

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

tcs logo
genpact logo
fico logo
flipkart logo
pwc logo
tata technologies
microsoft