4.8 (25,680) reviews 110,000
59,451*
NO COST EMI : 9,909 p.m for 6 Months
*Offer valid till 14th September 2025
Instructor Led Live Online
Self Learning + Live Mentoring
In - Person Classroom Training
MODULE 1: DATA SCIENCE ESSENTIALS
• Introduction to Data Science
• Evolution of Data Science
• Big Data Vs Data Science
• Data Science Terminologies
• Data Science vs AI/Machine Learning
• Data Science vs Analytics
MODULE 2: DATA SCIENCE DEMO
• Business Requirement: Use Case
• Data Preparation
• Machine learning Model building
• Prediction with ML model
• Delivering Business Value.
MODULE 3: ANALYTICS CLASSIFICATION
• Types of Analytics
• Descriptive Analytics
• Diagnostic Analytics
• Predictive Analytics
• Prescriptive Analytics
• EDA and insight gathering demo in Tableau
MODULE 4: DATA SCIENCE AND RELATED FIELDS
• Introduction to AI
• Introduction to Computer Vision
• Introduction to Natural Language Processing
• Introduction to Reinforcement Learning
• Introduction to GAN
• Introduction to Generative Passive Models
MODULE 5: DATA SCIENCE ROLES & WORKFLOW
• Data Science Project workflow
• Roles: Data Engineer, Data Scientist, ML Engineer and MLOps Engineer
• Data Science Project stages.
MODULE 6: MACHINE LEARNING INTRODUCTION
• What Is ML? ML Vs AI
• ML Workflow, Popular ML Algorithms
• Clustering, Classification And Regression
• Supervised Vs Unsupervised
MODULE 7: DATA SCIENCE INDUSTRY APPLICATIONS
• Data Science in Finance and Banking
• Data Science in Retail
• Data Science in Health Care
• Data Science in Logistics and Supply Chain
• Data Science in Technology Industry
• Data Science in Manufacturing
• Data Science in Agriculture
MODULE 1: PYTHON BASICS
• Introduction of python
• Installation of Python and IDE
• Python Variables
• Python basic data types
• Number & Booleans, strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators
MODULE 2: PYTHON CONTROL STATEMENTS
• IF Conditional statement
• IF-ELSE
• NESTED IF
• Python Loops basics
• WHILE Statement
• FOR statements
• BREAK and CONTINUE statements
MODULE 3: PYTHON DATA STRUCTURES
• Basic data structure in python
• Basics of List
• List: Object, methods
• Tuple: Object, methods
• Sets: Object, methods
• Dictionary: Object, methods
MODULE 4: PYTHON FUNCTIONS
• Functions basics
• Function Parameter passing
• Lambda functions
• Map, reduce, filter functions
MODULE 1: OVERVIEW OF STATISTICS
• Introduction to Statistics
• Descriptive And Inferential Statistics
• Basic Terms Of Statistics
• Types Of Data
MODULE 2: HARNESSING DATA
• Random Sampling
• Sampling With Replacement And Without Replacement
• Cochran's Minimum Sample Size
• Types of Sampling
• Simple Random Sampling
• Stratified Random Sampling
• Cluster Random Sampling
• Systematic Random Sampling
• Multi stage Sampling
• Sampling Error
• Methods Of Collecting Data
MODULE 3: EXPLORATORY DATA ANALYSIS
• Exploratory Data Analysis Introduction
• Measures Of Central Tendencies: Mean,Median And Mode
• Measures Of Central Tendencies: Range, Variance And Standard Deviation
• Data Distribution Plot: Histogram
• Normal Distribution & Properties
• Z Value / Standard Value
• Empirical Rule and Outliers
• Central Limit Theorem
• Normality Testing
• Skewness & Kurtosis
• Measures Of Distance: Euclidean, Manhattan And Minkowski Distance
• Covariance & Correlation
MODULE 4: HYPOTHESIS TESTING
• Hypothesis Testing Introduction
• P- Value, Critical Region
• Types of Hypothesis Testing
• Hypothesis Testing Errors : Type I And Type II
• Two Sample Independent T-test
• Two Sample Relation T-test
• One Way Anova Test
• Application of Hypothesis testing
MODULE 1: MACHINE LEARNING INTRODUCTION
• What Is ML? ML Vs AI
• Clustering, Classification And Regression
• Supervised Vs Unsupervised
MODULE 2: PYTHON NUMPY PACKAGE
• Introduction to Numpy Package
• Array as Data Structure
• Core Numpy functions
• Matrix Operations, Broadcasting in Arrays
MODULE 3: PYTHON PANDAS PACKAGE
• Introduction to Pandas package
• Series in Pandas
• Data Frame in Pandas
• File Reading in Pandas
• Data munging with Pandas
MODULE 4: VISUALIZATION WITH PYTHON - Matplotlib
• Visualization Packages (Matplotlib)
• Components Of A Plot, Sub-Plots
• Basic Plots: Line, Bar, Pie, Scatter
MODULE 5: PYTHON VISUALIZATION PACKAGE - SEABORN
• Seaborn: Basic Plot
• Advanced Python Data Visualizations
MODULE 6: ML ALGO: LINEAR REGRESSSION
• Introduction to Linear Regression
• How it works: Regression and Best Fit Line
• Modeling and Evaluation in Python
MODULE 7: ML ALGO: LOGISTIC REGRESSION
• Introduction to Logistic Regression
• How it works: Classification & Sigmoid Curve
• Modeling and Evaluation in Python
MODULE 8: ML ALGO: K MEANS CLUSTERING
• Understanding Clustering (Unsupervised)
• K Means Algorithm
• How it works : K Means theory
• Modeling in Python
MODULE 9: ML ALGO: KNN
• Introduction to KNN
• How It Works: Nearest Neighbor Concept
• Modeling and Evaluation in Python
MODULE 1: FEATURE ENGINEERING
• Introduction to Feature Engineering
• Feature Engineering Techniques: Encoding, Scaling, Data Transformation
• Handling Missing values, handling outliers
• Creation of Pipeline
• Use case for feature engineering
MODULE 2: ML ALGO: SUPPORT VECTOR MACHINE (SVM)
• Introduction to SVM
• How It Works: SVM Concept, Kernel Trick
• Modeling and Evaluation of SVM in Python
MODULE 3: PRINCIPAL COMPONENT ANALYSIS (PCA)
• Building Blocks Of PCA
• How it works: Finding Principal Components
• Modeling PCA in Python
MODULE 4: ML ALGO: DECISION TREE
• Introduction to Decision Tree & Random Forest
• How it works
• Modeling and Evaluation in Python
MODULE 5: ENSEMBLE TECHNIQUES - BAGGING
• Introduction to Ensemble technique
• Bagging and How it works
• Modeling and Evaluation in Python
MODULE 6: ML ALGO: NAÏVE BAYES
• Introduction to Naive Bayes
• How it works: Bayes' Theorem
• Naive Bayes For Text Classification
• Modeling and Evaluation in Python
MODULE 7: GRADIENT BOOSTING, XGBOOST
• Introduction to Boosting and XGBoost
• How it works?
• Modeling and Evaluation of in Python
MODULE 1: TIME SERIES FORECASTING - ARIMA
• What is Time Series?
• Trend, Seasonality, cyclical and random
• Stationarity of Time Series
• Autoregressive Model (AR)
• Moving Average Model (MA)
• ARIMA Model
• Autocorrelation and AIC
• Time Series Analysis in Python
MODULE 2: SENTIMENT ANALYSIS
• Introduction to Sentiment Analysis
• NLTK Package
• Case study: Sentiment Analysis on Movie Reviews
MODULE 3: REGULAR EXPRESSIONS WITH PYTHON
• Regex Introduction
• Regex codes
• Text extraction with Python Regex
MODULE 4: ML MODEL DEPLOYMENT WITH FLASK
• Introduction to Flask
• URL and App routing
• Flask application – ML Model deployment
MODULE 5: ADVANCED DATA ANALYSIS WITH MS EXCEL
• MS Excel core Functions
• Advanced Functions (VLOOKUP, INDIRECT..)
• Linear Regression with EXCEL
• Data Table
• Goal Seek Analysis
• Pivot Table
• Solving Data Equation with EXCEL
MODULE 6: AWS CLOUD FOR DATA SCIENCE
• Introduction of cloud
• Difference between GCC, Azure, AWS
• AWS Service ( EC2 instance)
MODULE 7: AZURE FOR DATA SCIENCE
• Introduction to AZURE ML studio
• Data Pipeline
• ML modeling with Azure
MODULE 8: INTRODUCTION TO DEEP LEARNING
• Introduction to Artificial Neural Network, Architecture
• Artificial Neural Network in Python
• Introduction to Convolutional Neural Network, Architecture
• Convolutional Neural Network in Python
MODULE 1: DATABASE INTRODUCTION
• DATABASE Overview
• Key concepts of database management
• Relational Database Management System
• CRUD operations
MODULE 2: SQL BASICS
• Introduction to Databases
• Introduction to SQL
• SQL Commands
• MY SQL workbench installation
MODULE 3: DATA TYPES AND CONSTRAINTS
• Numeric, Character, date time data type
• Primary key, Foreign key, Not null
• Unique, Check, default, Auto increment
MODULE 4: DATABASES AND TABLES (MySQL)
• Create database
• Delete database
• Show and use databases
• Create table, Rename table
• Delete table, Delete table records
• Create new table from existing data types
• Insert into, Update records
• Alter table
MODULE 5: SQL JOINS
• Inner Join, Outer Join
• Left Join, Right Join
• Self Join, Cross join
• Windows function: Over, Partition, Rank
MODULE 6: SQL COMMANDS AND CLAUSES
• Select, Select distinct
• Aliases, Where clause
• Relational operators, Logical
• Between, Order by, In
• Like, Limit, null/not null, group by
• Having, Sub queries
MODULE 7 : DOCUMENT DB/NO-SQL DB
• Introduction of Document DB
• Document DB vs SQL DB
• Popular Document DBs
• MongoDB basics
• Data format and Key methods
MODULE 1: GIT INTRODUCTION
• Purpose of Version Control
• Popular Version control tools
• Git Distribution Version Control
• Terminologies
• Git Workflow
• Git Architecture
MODULE 2: GIT REPOSITORY and GitHub
• Git Repo Introduction
• Create New Repo with Init command
• Git Essentials: Copy & User Setup
• Mastering Git and GitHub
MODULE 3: COMMITS, PULL, FETCH AND PUSH
• Code Commits
• Pull, Fetch and Conflicts resolution
• Pushing to Remote Repo
MODULE 4: TAGGING, BRANCHING AND MERGING
• Organize code with branches
• Checkout branch
• Merge branches
• Editing Commits
• Commit command Amend flag
• Git reset and revert
MODULE 5: GIT WITH GITHUB AND BITBUCKET
• Creating GitHub Account
• Local and Remote Repo
• Collaborating with other developers
MODULE 1: BIG DATA INTRODUCTION
• Big Data Overview
• Five Vs of Big Data
• What is Big Data and Hadoop
• Introduction to Hadoop
• Components of Hadoop Ecosystem
• Big Data Analytics Introduction
MODULE 2 : HDFS AND MAP REDUCE
• HDFS – Big Data Storage
• Distributed Processing with Map Reduce
• Mapping and reducing stages concepts
• Key Terms: Output Format, Partitioners,
• Combiners, Shuffle, and Sort
MODULE 3: PYSPARK FOUNDATION
• PySpark Introduction
• Spark Configuration
• Resilient distributed datasets (RDD)
• Working with RDDs in PySpark
• Aggregating Data with Pair RDDs
MODULE 4: SPARK SQL and HADOOP HIVE
• Introducing Spark SQL
• Spark SQL vs Hadoop Hive
MODULE 1: TABLEAU FUNDAMENTALS
• Introduction to Business Intelligence & Introduction to Tableau
• Interface Tour, Data visualization: Pie chart, Column chart, Bar chart.
• Bar chart, Tree Map, Line Chart
• Area chart, Combination Charts, Map
• Dashboards creation, Quick Filters
• Create Table Calculations
• Create Calculated Fields
• Create Custom Hierarchies
MODULE 2: POWER-BI BASICS
• Power BI Introduction
• Basics Visualizations
• Dashboard Creation
• Basic Data Cleaning
• Basic DAX FUNCTION
MODULE 3 : DATA TRANSFORMATION TECHNIQUES
• Exploring Query Editor
• Data Cleansing and Manipulation:
• Creating Our Initial Project File
• Connecting to Our Data Source
• Editing Rows
• Changing Data Types
• Replacing Values
MODULE 4: CONNECTING TO VARIOUS DATA SOURCES
• Connecting to a CSV File
• Connecting to a Webpage
• Extracting Characters
• Splitting and Merging Columns
• Creating Conditional Columns
• Creating Columns from Examples
• Create Data Model
Enrolling at DataMites was one of the best decisions I made for my career. Coming from a freelance writing background with no prior technical experience, I was initially unsure about stepping into the field of data analytics. But DataMites made the transition smooth and achievable. I’d highly recommend them to anyone looking for a guided, industry-ready data analytics course. A true DataMites success story!
Anyone with a basic understanding of mathematics and programming can enroll in a data science course in Gurgaon. Professionals looking to upskill or switch careers are also welcome. The course is suitable for individuals at various levels, from beginners to those with some experience in the field.
According to AmbitionBox reports, Data Scientist salaries in Gurgaon ranges from ₹5 lakhs to ₹30 lakhs, with the average salary being approximately ₹15 lakhs per year.
The best approach to studying data science in Gurgaon involves enrolling in reputable institutes that offer specialized courses, both online and offline. Gaining hands-on experience through projects and internships can also enhance practical knowledge. Networking with professionals through meetups and industry events can provide valuable insights and opportunities.
Data Science courses in Gurgaon typically span from 3 months to 1 year, depending on the program’s structure and level of depth. Short-term courses emphasize hands-on, practical skills, while longer programs provide comprehensive theoretical knowledge alongside real-world applications. The duration may also vary based on the chosen mode of study, including full-time, part-time, or online learning options.
Several reputable institutes in Gurgaon offer quality data science courses. DataMites stands out as one of the top choices, known for its comprehensive curriculum and expert trainers. Their practical approach and industry connections make it a leading option for aspiring data scientists.
Gurgaon is emerging as a key hub for data science, driven by the presence of numerous tech companies and startups. The demand for data professionals is expected to grow as businesses increasingly rely on data-driven decision-making. This trend suggests a promising future for data science careers in the region, with expanding opportunities.
To excel in data science in Gurgaon, proficiency in programming languages such as Python and R is essential. A solid understanding of machine learning algorithms, data visualization tools, and statistical analysis is also crucial. Additionally, knowledge of databases and cloud computing platforms enhances efficiency in handling large datasets.
The Certified Data Scientist course is highly regarded in Gurgaon for its comprehensive curriculum. It covers essential skills like machine learning, data analysis, and AI. This course offers industry-recognized certification, making it a top choice for aspiring data professionals.
Data science roles remain highly sought after in India, with projections indicating over 137,000 new positions by 2025.
In Gurgaon, the demand is particularly strong, with approximately 2,600 data science job listings as of February 2025.
This trend underscores the city's status as a key hub for data science professionals.
Yes, non-engineering graduates can transition into data science roles by developing key skills such as programming, statistics, and data analysis. Online courses, bootcamps, and hands-on projects can be effective pathways. With the right dedication and learning, diverse backgrounds can contribute valuable perspectives in the field.
Learning Python is not always a strict prerequisite for a data science course, but it is highly recommended. Many data science tools and libraries are Python-based, making it easier to work with datasets and models. Having Python knowledge can certainly enhance the learning experience.
To pursue a career in data science in Gurgaon, candidates typically need a background in computer science, statistics, or a related field. Proficiency in programming languages like Python or R, along with knowledge of machine learning algorithms, is essential. Additionally, strong problem-solving skills and a willingness to continuously learn and adapt are important.
The cost of a Data Science course in Gurgaon generally ranges from INR 15,000 to INR 2,50,000. Fees vary based on factors such as the course duration, curriculum depth, mode of learning, and certification provided. Prospective students should evaluate their learning goals and budget to choose a program that best suits their requirements.
Coding proficiency is highly beneficial in data science, as it enables the implementation of algorithms and data manipulation. While not always mandatory, a strong understanding of programming languages like Python or R enhances problem-solving capabilities. It allows data scientists to efficiently analyze, model, and interpret data.
Major ethical concerns in data science include privacy risks, as sensitive personal data may be misused or exposed. Bias in algorithms can lead to unfair outcomes, affecting marginalized groups. Additionally, lack of transparency in data collection and model decisions may undermine trust and accountability.
SQL plays a crucial role in data science by allowing efficient data retrieval, manipulation, and management from relational databases. It enables data scientists to query large datasets, perform aggregations, and filter information quickly. Mastery of SQL is essential for handling structured data and ensuring effective data analysis workflows.
Data science commonly utilizes tools like Python, R, and SQL for data analysis and manipulation. Technologies such as machine learning frameworks (e.g., TensorFlow, Scikit-learn) and data visualization tools (e.g., Tableau, Power BI) are also widely adopted. Additionally, cloud platforms like AWS and Azure are frequently used for scalable data storage and processing.
A data scientist course trains learners to build models, develop predictive algorithms, and extract insights from complex datasets. While data analysts focus on interpreting data to identify trends, data scientists create solutions that drive business strategy. In essence, analysts provide insights, and data scientists turn them into actionable innovations.
A data science course typically includes projects such as data cleaning, exploratory data analysis, and building predictive models. Students may also work on machine learning tasks and visualizing data insights. These projects aim to provide hands-on experience in real-world data challenges.
Gurgaon features key areas like Sector 17 (122001) and Sector 29 (122001), both bustling residential and commercial hubs, and DLF Phase 1 (122002), which hosts several educational institutes and training centers. Neighborhoods such as Sector 45 (122003), Sector 56 (122011), and Sector 57 (122011) offer a mix of residential and commercial spaces, making access to data science training convenient. The branch is also easily reachable from nearby localities including DLF Phase 2 (122002), DLF Phase 3 (122003), DLF Phase 4 (122003), and Sushant Lok (122002). Major areas in Gurgaon are well connected, providing easy access for students and professionals pursuing data science courses with hands-on training and practical applications.
In the finance sector, Data Science is applied for fraud detection, risk evaluation, and algorithmic trading to maximize returns. It also supports customer analytics and personalized service offerings. Overall, it empowers financial institutions to make informed, data-driven decisions and efficiently manage investment portfolios.
In a Data Science course in Gurgaon, you’ll learn how to analyze and interpret data using Python, SQL, and machine learning. You’ll work on real projects to clean, visualize, and model data for practical insights. The course also covers statistics, big data tools, and deployment skills to make you industry-ready.
After completing the Certified Data Scientist Course in Gurgaon, an individual will be thoroughly equipped with the following skills:
Data science is increasingly integrating AI to automate data analysis, enhancing efficiency and accuracy. Machine learning models and AI algorithms enable deeper insights from larger datasets. This evolution is driving more data-driven decision-making across industries.
Anyone with a basic understanding of mathematics and programming is eligible to enroll in DataMites' Data Science course in Gurgaon. The program is open to both beginners and professionals looking to enhance their skills. No prior experience in data science is required, but a keen interest in the field is essential.
DataMites in Gurgaon offers a 100% money-back guarantee if you request a refund within one week of the course start date and attend at least two sessions during the first week. Refunds are not available after six months from the course enrollment date. Exam bookings through external certification bodies are non-refundable.
Yes, DataMites in Gurgaon offers data science courses that include internship opportunities. These internships provide practical experience under the guidance of industry experts. Upon completion, participants receive both internship and experience certificates.
Yes, DataMites Gurgaon offers EMI options for our Data Science course. This allows students to pay in easy installments, making it more convenient. Interested candidates can inquire about the available EMI plans for further details.
DataMites offers Data Science courses in Gurgaon with fees ranging from INR 40,000 to INR 1,20,000, depending on the chosen learning mode and course duration. The Live Virtual Instructor-Led Online course is priced at INR 59,451, while the Classroom In-Person Training is available for INR 64,451. The Blended Learning option, combining self-learning with live mentoring, is offered at INR 34,951.
Yes, DataMites Gurgaon offers a Data Science course that includes placement assistance. The program is designed to help students gain relevant skills and secure job opportunities in the field. Placement support is provided to enhance career prospects after course completion.
The DataMites data science syllabus covers essential topics such as data preprocessing, statistical analysis, machine learning algorithms, and deep learning. It also includes tools like Python, SQL, and Tableau for data visualization and analysis. The curriculum is designed to provide a comprehensive foundation in data science and practical problem-solving skills.
DataMites primarily offers online training for its courses in Gurgaon. Offline sessions are available upon request if there is sufficient demand. For more details, please refer to our official website.
DataMites offers free demo classes for our Data Science courses in Gurgaon. These sessions provide an overview of the curriculum and teaching methodology. For the most current schedule and registration details, please visit our official website or contact our Gurgaon center directly.
DataMites offers a comprehensive curriculum designed to provide in-depth knowledge of data science, backed by experienced instructors. Their practical approach ensures hands-on learning, helping students apply concepts in real-world scenarios. Additionally, DataMites has a strong placement support system, aiding career growth post-course completion.
DataMites in Gurgaon offers courses that incorporate live projects. For instance, our Artificial Intelligence program includes 10 capstone projects and 1 client project to provide practical experience. Similarly, the Data Science course offers 20 capstone projects and 3 client projects, ensuring hands-on learning opportunities.
DataMites Gurgaon / Gurugram is easily accessible from key areas such as Sector 17 (122001) and Sector 29 (122001), prominent commercial and residential hubs, and DLF Phase 1 (122002), a well-established neighborhood. Areas like Sector 45 (122003), Sector 56 (122011), and Sector 57 (122011) offer convenient access to training centers. The branch is also well connected to nearby localities including DLF Phase 2 (122002), DLF Phase 3 (122003), Sushant Lok (122002), and Sohna Road (122018), making it easy for students and professionals to enroll in DataMites courses.
DataMites offers a Data Science course in Gurgaon with a duration of 8 months, totaling 700 learning hours. The program includes 120 hours of live online training, complemented by 25 capstone projects and one client project. Additionally, students receive 365 days of access to a cloud lab and benefit from internship and job assistance.
Yes, DataMites Gurgaon offers course certification upon completion. The certifications are aligned with IABAC and NASSCOM FutureSkills standards. These credentials can help enhance your professional profile and skills in the data science field.
DataMites in Gurgaon offers courses led by experienced trainers, including Ashok Veda, a globally recognized AI expert with 19 years in analytics and data science. These instructors provide comprehensive training in data science, machine learning, and related fields. Their expertise ensures that students receive quality education aligned with industry standards.
DataMites in Gurgaon offers multiple payment options for course fees, including cash, net banking, checks, debit cards, credit cards, PayPal, Visa, MasterCard, and American Express. This variety allows students to choose the most convenient method for their transactions. For personalized assistance or to explore installment plans, it is recommended to contact us directly.
The Certified Data Scientist course is a comprehensive program that builds expertise in data analysis, machine learning, and data visualization. It provides hands-on training with large datasets and real-world projects to develop practical skills. Upon completion, participants earn a recognized certification that validates their proficiency in data science.
DataMites in Gurgaon offers a variety of courses, including Data Science, Machine Learning, Artificial Intelligence, Data Analytics, and Python programming. These programs are designed to equip individuals with the skills needed for careers in data-driven fields. Each course combines theoretical knowledge with practical applications to ensure comprehensive learning.
The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -
The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.
No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.
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