4.9 (24,658) reviews 110,000
59,451*
NO COST EMI : 9,909 p.m for 6 Months
*Offer valid till 9th November 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!
The Data Science Course fees in Navi Mumbai usually range from INR 15,000 to INR 2,50,000. The total cost depends on factors like the institute, duration of the program, and the chosen learning mode, including online, classroom, or hybrid options.
According to AmbitionBox, Data Scientists in Navi Mumbai earn between INR 4 Lakhs and INR 20 Lakhs per year, with an average annual salary of around INR 12 Lakhs for professionals with 1 to 6 years of experience, making it a lucrative and promising career path.
The scope of Data Science in Navi Mumbai is steadily increasing, fueled by the city’s expanding technology sector and rising demand for data-driven solutions. With numerous opportunities across industries and attractive salary prospects, it promises a strong and rewarding career future.
Eligibility for Data Science courses in Navi Mumbai usually includes a bachelor’s degree in a relevant field like Engineering, Computer Science, Mathematics, or Statistics. Applicants with logical thinking, analytical aptitude, and basic programming knowledge are preferred, though institutes often provide beginner-friendly training to help newcomers build these skills.
Courses in Navi Mumbai typically range from 3 months to 1 year in duration. Short-term programs emphasize practical skill development, while longer courses include comprehensive learning through theory, projects, and real-time applications. Learners can choose from flexible study options such as full-time, part-time, or online modes to suit their schedules.
The most effective way to learn Data Science in Navi Mumbai is by joining a trusted training institute that blends concept-based learning with real-world project experience. Engaging in practical exercises, using industry-relevant tools, and exploring internships or live case studies helps learners gain the applied knowledge and confidence needed to excel in the field.
Several institutes in Navi Mumbai offer quality Data Science training, but DataMites stands out for its in-depth curriculum, practical projects, globally recognized certifications, expert mentorship, and dedicated placement support. Other reputed institutes in the city also provide specialized programs in areas like Artificial Intelligence, Machine Learning, and Python development.
A certified data scientist course is often considered the best, as it provides structured learning and credible credentials, covering essential topics like machine learning, data analysis, and programming tools widely used in the industry.
Anyone interested in building a career in analytics or technology can enroll in a Data Science course in Navi Mumbai. It is ideal for students, working professionals, and career changers from backgrounds such as IT, engineering, mathematics, statistics, or business who want to develop data-driven decision-making and technical skills.
Yes, data science professionals are in high demand across Navi Mumbai as companies increasingly rely on data-driven insights for decision-making. With a growing number of openings in IT, finance, and analytics sectors, the city offers strong employment prospects for skilled data science experts.
Yes, non-engineers can successfully transition to a Data Science Course in Navi Mumbai. With the right training in programming, statistics, and analytical tools, individuals from backgrounds like commerce, economics, mathematics, or business can build the necessary skills. Many institutes also offer beginner-friendly courses designed to help non-technical learners enter the field confidently.
Yes, Python is an essential part of most Data Science courses in Navi Mumbai. It is widely used for data analysis, machine learning, and visualization due to its simplicity and extensive libraries. Learning Python helps students efficiently handle data, build models, and implement practical solutions across real-world projects.
Yes, coding is an important skill for building a Data Science career in Navi Mumbai. While advanced programming isn’t mandatory at the start, a good understanding of languages like Python, R, or SQL helps in data manipulation, model building, and automation. Many training programs also teach coding from the basics, making it accessible for beginners.
A successful Data Science career in Navi Mumbai requires a mix of technical and analytical skills. Key competencies include proficiency in Python or R, knowledge of statistics and mathematics, data visualization, machine learning, and SQL. In addition, strong problem-solving ability, critical thinking, and communication skills are essential for interpreting data insights and applying them to real-world business challenges.
The key components of Data Science include data collection, data cleaning, data analysis, and data visualization. It also involves applying statistical methods, machine learning algorithms, and predictive modeling to extract insights from large datasets. Together, these components enable data-driven decision-making and help organizations solve complex business problems effectively.
The latest trends in Data Science in Navi Mumbai include increased adoption of artificial intelligence, automation, and cloud-based analytics. Companies are focusing on real-time data processing, predictive modeling, and AI-driven decision-making, creating growing demand for skilled data professionals in the region.
Key ethical concerns in Data Science include maintaining data privacy, preventing algorithmic bias, and ensuring transparency in model decisions. Professionals must also handle sensitive data responsibly, obtain proper consent, and use data-driven insights in ways that promote fairness and accountability.
To become a Data Scientist in Navi Mumbai, one should start by gaining a strong foundation in mathematics, statistics, and programming. Enrolling in a structured Data Science course that offers hands-on projects, mentorship, and placement support is highly beneficial. Building a portfolio with real-world projects, internships, and certifications further enhances employability in the city’s growing data-driven job market.
SQL plays a vital role in data science by enabling efficient data extraction, manipulation, and analysis from databases. It helps data scientists organize and query large datasets, making it easier to generate insights and support data-driven decisions.
A Certified Data Scientist course is a structured training program designed to develop core skills in data analysis, machine learning, and statistical modeling. It provides hands-on learning through real-world projects and is often accredited by recognized bodies, helping learners gain industry-recognized credentials that enhance career opportunities in data-driven fields.
The Data Science course in Navi Mumbai offers flexible learning options to suit various preferences:
These fees are subject to change; for the most current information, please refer to our official website.
DataMites offers a Certified Data Scientist course in Navi Mumbai with a duration of 8 months, comprising 700 learning hours. The program includes 120 hours of live online training, 25 capstone projects, and 1 client project. This comprehensive curriculum is designed to equip students with practical skills and industry-relevant knowledge.
Yes, DataMites in Navi Mumbai provides a Data Science course that includes placement assistance to help learners transition into industry roles. The institute supports students through internship opportunities, resume building, and interview preparation, enhancing their chances of securing suitable data science positions after course completion.
Yes, DataMites offers EMI options for the Data Science course in Navi Mumbai, allowing you to pay the fee in manageable installments. Additionally, other payment methods such as credit card, debit card, and online payment are also available.
Yes, DataMites offers free demo classes for our courses in Navi Mumbai. You can contact us directly to schedule a demo session or get more details. For further information, visiting our official website is recommended.
DataMites offers a data science course that includes an internship and a chance to gain real-world experience. The program is designed to provide learners with essential skills and an internship opportunity. This allows participants to apply their knowledge in a practical setting and enhance their career prospects.
DataMites offers a 100% money-back guarantee if you request a refund within one week of the course start date and have attended at least two sessions. Refunds are not available after six months or if more than 30% of the material has been accessed. For detailed information, please refer to DataMites' refund policy.
Anyone with an interest in Data Science can enroll in DataMites courses in Navi Mumbai. The courses are open to individuals from various educational backgrounds, including beginners and professionals looking to upskill. DataMites offers flexible learning options to accommodate diverse learning needs and career goals.
DataMites offers Data Science courses to learners in Navi Mumbai and surrounding localities through convenient online and blended learning options. Individuals residing in areas like Vashi (400703), Nerul (400706), Kharghar (410210), Belapur (400614), Airoli (400708), Ghansoli (400701), Kopar Khairane (400709), Seawoods (400706), and Panvel (410206) can easily access these training programs. For information on admissions, class schedules, and course fees, students can directly reach out to DataMites.
DataMites offers a comprehensive Data Science curriculum designed to provide practical skills and industry-relevant knowledge. Our expert trainers guide students through real-world applications using advanced tools and technologies. With flexible learning options, DataMites ensures a personalized and efficient learning experience.
The trainers at DataMites in Navi Mumbai are experienced professionals with strong expertise in data science and related fields. They possess both academic qualifications and industry experience to provide practical insights. DataMites ensures that trainers deliver quality learning through real-world applications and hands-on training.
DataMites offers course certification upon successful completion of its programs. The certifications are recognized and accredited by renowned bodies like IABAC and NASSCOM FutureSkills. These certifications help validate the skills acquired and enhance career prospects.
The DataMites Flexi-Pass provides learners with a 3-month flexible window to attend Data Science training sessions. It allows participants to revisit lessons, clear doubts, and reinforce concepts at their own pace, ensuring continuous guidance and a seamless learning journey.
The DataMites Data Science syllabus covers essential topics like Python programming, statistics, machine learning, data visualization, and model deployment. It emphasizes practical learning through real-world projects, ensuring learners gain both technical expertise and industry-relevant problem-solving skills.
DataMites Navi Mumbai provides flexible payment methods for students. Payment can be made through debit/credit cards such as Visa, MasterCard, and American Express, along with PayPal. EMI options are also available, offering a convenient way to pay in installments.
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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