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Data Science Training Course in Nashik With GEN AI by Uncodemy

Become a professional with the Best Data Science Training Institute in Nashik call Uncodemy.

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Program Details

Data Science with AI — Training & Placement Program Master Data Science from Fundamentals to Advanced AI Applications

A comprehensive 8-9 months industry-focused training program designed to build strong Data Science, Machine Learning & Gen-AI skills through real-time projects, personalized mentoring, and dedicated placement support that prepares you for top-tier data-driven roles.

  • 🤖 Core Skills Covered: Python, Statistics, Machine Learning, Deep Learning, Gen AI, NLP
  • ⏱️ Program Duration: 8-9 Months
  • 💼 Average Salary Package: ₹8–28 LPA
  • 🚀 Placement Support: Guaranteed Interview Opportunities + Resume & Interview Preparation
  • 🏢 Placement Drives: With Top MNCs & High-Growth Startups
  • 🎯 Career Paths: Data Scientist, ML Engineer, AI Engineer, Data Researcher

Curriculums for Data Science Training Course in Nashik

Data Science Curriculum

The curriculum has been designed by faculty from IITs, and Expert Industry Professionals.

time
150+

Hours of Content

live1-removebg-preview
90+

Live Sessions

tools
15+

Tools and Software

Set the Basics Right

Data science is the domain of study that deals with vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions. For example, finance companies can use a customer's banking and bill-paying history to assess creditworthiness and loan risk.

Data science course provider of Nashik called Uncodemy offers a curriculum that contains following courses to strengthen your skill in Data Science-

1. Python for Data Science

  • Need for Programming
  • Advantages of Programming
  • Overview of Python
  • Organizations using Python
  • Python Applications in Various Domains
  • Python Installation
  • Variables
  • Operands and Expressions
  • Conditional Statements
  • Loops
  • Command Line Arguments
  • Method of Accepting User Input and eval Function
  • Python - Files Input/Output Functions
  • Lists and Related Operations
  • Tuples and Related Operations
  • Strings and Related Operations
  • Sets and Related Operations
  • Dictionaries and Related Operations
  • User-Defined Functions
  • Concept of Return Statement
  • Concept of name=” main ”
  • Function Parameters
  • Different Types of Arguments
  • Global Variables
  • Global Keyword
  • Variable Scope and Returning Values
  • Lambda Functions
  • Various Built-In Functions
  • Introduction to Object-Oriented Concepts
  • Built-In Class Attributes
  • Public, Protected and Private Attributes, and Methods
  • Class Variable and Instance Variable
  • Constructor and Destructor
  • Decorator in Python
  • Core Object-Oriented Principles
  • Inheritance and Its Types
  • Method Resolution Order
  • Overloading
  • Overriding
  • Getter and Setter Methods
  • Inheritance-In-Class Case Study
  • Standard Libraries
  • Packages and Import Statements
  • Topics : Working with Modules and Handling Exceptions
  • Info@uncodemy.com | +91-9818366550 | www.uncodemy.com
  • Reload Function
  • Important Modules in Python
  • Sys Module
  • Os Module
  • Math Module
  • Date-Time Module
  • Random Module
  • JSON Module
  • Regular Expression
  • Exception Handling
  • Basics of Data Analysis
  • NumPy - Arrays
  • Operations on Arrays
  • Indexing Slicing and Iterating
  • NumPy Array Attributes
  • Matrix Product
  • NumPy Functions
  • Functions
  • Array Manipulation
  • File Handling Using NumPy
  • Array Creation and Logic Functions
  • File Handling Using Numpy
  • Introduction to pandas
  • Data structures in pandas
  • Series
  • Data Frames
  • Importing and Exporting Files in Python
  • Basic Functionalities of a Data Object
  • Merging of Data Objects
  • Concatenation of Data Objects
  • Types of Joins on Data Objects
  • Data Cleaning using pandas
  • Exploring Datasets

    • 2. Data Science Primer and Statistics

  • What is Data Science?
  • What does Data Science involve?
  • Era of Data Science
  • Business Intelligence vs Data Science
  • Life cycle of Data Science
  • Tools of Data Science
  • Application of Data Science
  • Introduction
  • Stages of Analytics
  • CRISP DM Data Life Cycle
  • Data Types
  • Introduction to EDA
  • First Business Moment Decision
  • Second Business Moment Decision
  • Third Business Moment Decision
  • Fourth Business Moment Decision
  • Correlation
  • What is Feature
  • Feature Engineering
  • Feature Engineering Process
  • Benefit
  • Feature Engineering Techniques
  • Basics Of Probability
  • Discrete Probability Distributions
  • Continuous Probability Distributions
  • Central Limit Theorem
  • Concepts Of Hypothesis Testing - I: Null And Alternate Hypothesis, Making
  • A Decision, And Critical Value Method
  • Concepts Of Hypothesis Testing - II: P-Value Method And Types Of Errors
  • Industry Demonstration Of Hypothesis Testing: Two-Sample Mean And
  • Proportion Test, A/B Testing

    • 3. Machine Learning

  • Simple Linear Regression
  • Simple Linear Regression In Python
  • Multiple Linear Regression
  • Multiple Linear Regression In Python
  • Industry Relevance Of Linear Regression
  • Univariate Logistic Regression
  • Multivariate Logistic Regression: Model
  • Building And Evaluation
  • Logistic Regression:
  • Industry Applications
  • Data mining classifier technique
  • Application of KNN classifier
  • Lazy learner classifier
  • Altering hyperparameter(k) for better accuracy
  • Black box
  • SVM hyperplane
  • Max margin hyperplane
  • Kernel tricks for non linear spaces
  • Rule based classification method
  • Different nodes for develop decision trees
  • Discretization
  • Entropy
  • Greedy approach
  • Information gain
  • Challenges with standalone model
  • Reliability and performance of a standalone model
  • Homogeneous & Heterogeneous Ensemble Technique
  • Bagging & Boosting
  • Random forest
  • Stacking
  • Voting & Averaging technique
  • Difference between cross sectional and time series data
  • Different component of time series data
  • Visualization techniques for time series data
  • Model based approach
  • Data driven based approach
  • Difference between Supervised and Unsupervised Learning
  • Prelims of clustering
  • Measuring distance between record and groups
  • Linkage functions
  • Dendrogram
  • Dimension reduction
  • Application of PCA
  • PCA & its working
  • SVD & its working
  • Point of Sale
  • Application of Association rules
  • Measure of association rules
  • Drawback of measure of association rules
  • Condition probability
  • Lift ratio

    • 4. Deep Learning

  • Black box techniques
  • Intution of neural networks
  • Perceptron algorithm
  • Calculation of new weights
  • Non linear boundaries in MLP
  • Integration function
  • Activation function
  • Error surface
  • Gradient descent algo
  • Imagenet classification challenges
  • Convolution network applications
  • Challenges in classifying the images using MLP
  • Parameter explosion
  • Pooling layers
  • Fully connected layers
  • Alexnet case study
  • Modelling sequence data
  • Vanishing/Gradient descent explode
  • What is a Deep Learning Platform?
  • H2O.ai
  • Dato GraphLab
  • What is a Deep Learning Library?
  • Theano
  • Deeplearning4j
  • Torch
  • Caffe

    • 5. Data Visualization and Story Telling

  • Bar Charts
  • Histograms
  • Pie Charts
  • Box Plots
  • Scatter Plots
  • Line Plots and Regression
  • Pair plot
  • Word Clouds
  • Radar Charts
  • Waffle Charts

    • 6. Natural Language Processing

  • Text data generating sources
  • How to give structure to text structure using bag of words
  • Terminology used in text data analysis
  • DTM & TDM
  • TFIDF & its usage
  • Word cloud and its interpretation

    • 7. SQL

  • Introduction to Databases
  • How to create a Database instance on Cloud?
  • Provision a Cloud hosted Database instance.
  • What is SQL?
  • Thinking About Your Data
  • Relational vs. Transactional Models ER Diagram
  • CREATE Table Statement and DROP tables
  • UPDATE and DELETE Statements
  • Retrieving Data with a SELECT Statement
  • Creating Temporary Tables
  • Adding Comments to SQL
  • Basics of Filtering with SQL
  • Advanced Filtering: IN, OR, and NOT
  • Using Wildcards in SQL
  • Sorting with ORDER BY
  • Math Operations
  • Aggregate Functions
  • Grouping Data with SQL
  • Using Subqueries
  • Subquery Best Practices and Considerations
  • Joining Tables
  • Cartesian (Cross) Joins
  • Inner Joins
  • Aliases and Self Joins
  • Advanced Joins: Left, Right, and Full Outer Joins
  • Unions
  • Working with Text Strings
  • Working with Date and Time Strings
  • Date and Time Strings Examples
  • Case Statements
  • Views
  • Data Governance and Profiling
  • Using SQL for Data Science
  • How to access databases using Python?
  • Writing code using DB-API
  • Connecting to a database using DB API
  • Create Database Credentials
  • Connecting to a database instance
  • Creating tables, loading, inserting, data and querying data
  • Analysing data with Python

    • 8. Excel

  • Input data & handling large spreadsheets
  • Tricks to get your work done faster
  • Automating data analysis (Excel VLOOKUP, IF Function, ROUND and more)
  • Transforming messy data into shape
  • Cleaning, Processing and Organizing large data
  • Spreadsheet design principles
  • Drop-down lists in Excel and adding data validation to the cells.
  • Creating Charts & Interactive reports with Excel Pivot Tables, PivotCharts, Slicers and Timelines
  • Functions like: - COUNTIFS, COUNT, SUMIFS, AVERAGE and many more.
  • Excel features: - Sort, Filter, Search & Replace Go to Special etc...
  • Importing and Transforming data (with Power Query)
  • Customize the Microsoft Excel interface
  • Formatting correctly for professional reports.
  • Commenting on cells.
  • Automate data entry with Autofill and Flash-fill.
  • Writing Excel formulas & referencing to other workbooks / worksheets.
  • Printing options
  • Charts beyond column and bar charts: - Pareto chart, Histogram, Treemap, Sunburst
  • charts & more

    • 9. Tableau

  • Introduction to Data Visualization
  • Tableau Introduction and Tableau Architecture
  • Exploring Data using Tableau
  • Working with Data using Tableau including Data Extraction and
  • Blending
  • Various Charts in Tableau(Basics to Advanced)
  • Sorting-Quick Sort, Sort from Axis, Legends, Axis, Sort by Fields
  • Filtering- Dimension Filters, Measure Filters, Date Filters, Tableau
  • Context Filters
  • Groups , Sets and Combined Sets
  • Reference Lines, Bands and Distribution
  • Parameters, Dynamic Parameters and Actions
  • Forecasting-Exponential Smoothening Techniques
  • Clustering
  • Calculated Fields in Tableau, Quick Tables
  • Tableau Mapping Features
  • Tableau Dashboards, Dashboards Action and Stories

    • 10. Power BI

  • Introduction to Power BI – Need, Imprtance
  • Power BI – Advantages and Scalable Options
  • Power BI Data Source Library and DW Files
  • Business Analyst Tools, MS Cloud Tools
  • Power BI Installation
  • Power BI Desktop – Instalation, Usage
  • Sample Reports and Visualization Controls
  • Understanding Desktop & Mobile Editions
  • Report Rendering Options and End User Access
  • Report Design with Databse Tables
  • Report Visuals, Fields and UI Options
  • Reports with Multiple Pages and Advantages
  • Pages with Multiple Visualizations. Data Access
  • “GET DATA” Options and Report Fields, Filters
  • Report View Options: Full, Fit Page, Width Scale
  • Report Design using Databases & Queries

    • Get Your Data Scientist Certification in Nashik

    To become a certified Data Science professional, it’s essential to be trained by experts. Uncodemy offers an Advanced Data Scientist Training in Nashik, delivered by certified trainers from the Data Science industry. This certification is crucial for landing high-salaried positions in leading companies.

    Following are the Data Science course benefits in Nashik :
    • Industry-Recognized:Enhance your resume with a certification valued by employers.
    • Career Advancement:Open new job opportunities and career paths in Data Science.
    • Skill Development:Master tools and technologies such as Python, R, SQL, and more.

    Uncodemy provides Data Science Certification Course in Nashik, in association with ISO, NASSCOM, and Skill India.

    Tools and Technologies covered
    • imageexcelExcel
    • imagetablueTableau
    • Power-BI-SymbolPower-Bi
    • imageggplotggplot
    • imagejupitorJupyter
    • imagenumpyNumpy
    • imagepythonPython
    • imagepandasPandas
    • imageseabornSeaborn
    • imagelockerLooker
    • Matplotlib-logoMatplotlib
    • imagepycharmPyCharm
    • imagegoogleColabGoogle Colab
    • imageanacondaAnaconda
    • imagenltkNLTK
    • imagescikitlernScikit-learn
    • imagesqlSQL
    • imageMySqlMySql
    • imagepostgersqlPostgreSQL
    • imagemlML
    • imagedeeplDeep Learning
    • imagenlpNLP
    Uncodemy helping students to Ace Their Interview-

    Uncodemy, the Best Data Science institute in Nashik, equips students with essential skills and strategies to excel in interviews at any level. Our provisions include:

    Deep Insight to Data science Industry with the Live Projects

    Uncodemy, the Best Data Science training institute in Nashik, offers top-notch instruction from industry experts in the latest Data Science trends and subjects. Uncodemy provides a comprehensive experience to the students by the below mentioned Data Science Course Benefits in Nashik:

    Become a Data Scientist - Talk to Expert Counselor

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    What's Included in our Program
    Training with Industry Expert Trainer
    Live Projects ( Multiple Domain)
    Resume Building & Grooming Session
    Interview & Mock Interview Session
    3-6 Months Internship Certificate
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    What's Included in our Program
    Training with Industry Expert Trainer
    Live Projects ( Multiple Domain)
    Resume Building & Grooming Session
    Interview & Mock Interview Session
    3-6 Months Internship Certificate
    Any QueriesConnect with us for Counselling
    Call or Whatsapp
    +91 9818366550
    Schedule a Demo Session Now
    Application Form

    Our Student Success Stories

    Join thousands of students who transformed their careers with Uncodemy and landed dream jobs at top companies

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    Divya Pandey - Placed at Qudys as Data Quality Analyst - 8.5 LPA
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    Shweta Nigam - Placed at F15 as Business Analyst - 6.8 LPA
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    Nikhil Sawran - Placed at Jetking Technologies as Technical Trainer - 4.44 LPA
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    Rituraj - Placed at Embassy Services (HCL) as MIS Executive - 3.5 LPA
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    HIGHEST
    Sweety - Placed at Infosys as Scrum Master - 18 LPA
    Sweety
    Infosys
    18 LPA
    Scrum Master
    TOP PLACEMENT
    Akshay Patil - Placed as Data Scientist - 14 LPA
    Akshay Patil
    14 LPA
    Data Scientist
    TOP PLACEMENT
    Farhan Noman - Placed at Cubastion as Senior Associate Consultant - 9.5 LPA
    Farhan Noman
    Cubastion
    9.5 LPA
    Senior Associate Consultant
    TOP PLACEMENT
    Divya Pandey - Placed at Qudys as Data Quality Analyst - 8.5 LPA
    Divya Pandey
    Qudys
    8.5 LPA
    Data Quality Analyst
    TOP PLACEMENT
    Shahil Growar - Placed at Midland Credit Management as Senior Marketing Analyst - 7.5 LPA
    Shahil Growar
    Midland Credit
    7.5 LPA
    Senior Marketing Analyst
    TOP PLACEMENT
    Shweta Nigam - Placed at F15 as Business Analyst - 6.8 LPA
    Shweta Nigam
    F15
    6.8 LPA
    Business Analyst
    TOP PLACEMENT
    Saniya Agarwal - Placed at Fiserv as Business Analyst - 6.5 LPA
    Saniya Agarwal
    Fiserv
    6.5 LPA
    Business Analyst
    TOP PLACEMENT
    Rupali Ojha - Placed at HSBC as Business Analyst - 5.5 LPA
    Rupali Ojha
    HSBC
    5.5 LPA
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    Placed at Capaeminia - 5.5 LPA
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    Pawan Mehra - Placed at upGrad as MIS Analyst - 5.0 LPA
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    Fatima - Placed at Cess Meditech as Business Analyst - 4.8 LPA
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    Neeva Shah - Placed at Make as Business Analyst - 4.5 LPA
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    Neeva Shah - Placed at Make as Business Analyst - 4.5 LPA
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    Nikhil Sawran - Placed at Jetking Technologies as Technical Trainer - 4.44 LPA
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    Mehak Khan - Placed at Clarivate as IP Renewals Analyst - 4 LPA
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    Kundan Kumar Kushwaha - Placed at FabricRear as MIS Executive - 3.5 LPA
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    Rituraj - Placed at Embassy Services (HCL) as MIS Executive - 3.5 LPA
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    Rohit Yashwant Dhulankar - Placed at BrownWall as Purchase Executive - 3.24 LPA
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    Kartikeya - Placed at MarkScan as Research Analyst - 3 LPA
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    Yash - Placed at BIZS Technologies as Business Analyst - 3 LPA
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