4.9 (26,850) reviews 110,000
59,451*
NO COST EMI : 9,909 p.m for 6 Months
*Offer valid till 17th May 2026
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
I joined DataMites for the Certified Data Scientist online course, and it was a great experience! The real-time projects helped me apply my learning practically, and the placement support added real value to my career restart after 8 years. DataMites is the perfect platform to learn, grow, and begin your data science journey.
I joined DataMites for the Data Science course and learned Python, SQL, Machine Learning, and Deep Learning through hands-on projects. The trainers are excellent at explaining concepts clearly. The placement team is very supportive and provides great opportunities thanks to DataMites for helping me start my data science journey.
I joined DataMites after my B.Tech when I developed an interest in Data Science and Machine Learning. The training was well-structured, and I even got an internship opportunity that helped me gain real experience. The placement team was super supportive and guided me through every step. Thanks to DataMites, I’m now placed at Horizon Broadband Pvt. Ltd.
I joined DataMites after completing my BCA, and it was the best decision for my data science career! I learned Python, SQL, Machine Learning, Deep Learning, and NLP, and worked on several capstone and client projects that gave me real-world experience. The trainers and team were always friendly and supportive, patiently clearing all my doubts. Thanks to DataMites, I’m confident and job-ready in data science
I started my data science journey with DataMites, and it’s been an amazing experience! The Certified Data Scientist Program helped me learn everything from scratch through hands-on projects and an internship. The placement team was incredibly supportive, always ready to clarify my doubts. Thanks to their guidance, I successfully got placed. Highly recommend DataMites to anyone starting their data science career
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 knowledge of mathematics and statistics can apply. These programs are open to both recent graduates and working professionals. Having coding experience is beneficial, though not always required.
Hyderabad has several reputed training centers, but DataMites Institute stands out as a strong choice. It provides structured learning, industry-recognized certifications, and hands-on projects under expert mentorship. With the added advantage of career support, it proves to be a dependable option for building a career in data science.
To excel in Data Science in Hyderabad, professionals should develop proficiency in Python, R, and SQL for effective data management and analysis. A solid understanding of machine learning, statistics, and data visualization is crucial for generating valuable insights. Additionally, knowledge of big data tools, AI frameworks, and cloud platforms can significantly expand career opportunities.
The Certified Data Scientist Course is a leading Data Science program in Hyderabad. It includes training in machine learning, deep learning, statistics, and practical projects to build industry-ready skills. This certification strengthens career prospects by preparing learners for data-driven roles across diverse sectors.
Yes. Demand for data science professionals in Hyderabad remains strong as organizations increasingly depend on data-driven insights. With AI, machine learning, and analytics shaping business strategies, career opportunities are expected to grow consistently in the coming years.
Data Science is all about managing a set of information received from various sources, to arrive at conclusions. The data that is acquired needs to be analysed and decisions need to be taken. Statistics makes it easier to work on data. Various statistical techniques such as Classification, Regression, Hypothesis Testing, Time Series Analysis is used to construct data models. With the help of Statistics, a Data Scientist can gain better insights, which enables to effectively streamline the decision-making process.
The different roles, Data Science is subjected to, in an organisation.
Analysing and managing projects.
Employing various data models.
Making use of sampling techniques
Prediction and Analysis
Segmentation through clustering technique
Making use of Linear and Logistics regression methods
Data Science is a vast subject for study, it is a mix of Statistics and Computer Science. DataMites in Hyderabad, offers quality training sessions in Data Science, Artificial Intelligence, Machine Learning etc. The data science courses provided by DataMites in Hyderabad are exclusively designed in tune with the current industry requirements. Also with many projects to work on, under the mentoring of industry experts.
Yes, programming is an essential aspect of the role. Python and SQL are the primary languages used, and a beginner-level understanding is sufficient to get started. With experience, advanced coding skills enable professionals to handle more complex challenges effectively.
Hyderabad is one of the technological hubs of India, with lots of business opportunities and large corporate houses adorning the city. This, in turn, contributes to new employment opportunities being created. Hence opting for a Data Science course in Hyderabad will help an individual to leverage the available possibilities in the best manner, to land a career in Data Science.
Data Scientists have been in great demand in Hyderabad. As an acknowledgement to this rising demand, DataMites has come with the Certified Data Scientist course in Hyderabad. The course covers all the areas of Data Science, Machine Learning, basics of Mathematics and Statistics, etc. Also, the Certified Data Scientist course, covers all the practical aspects of the knowledge required to become a Data Scientist.
Hyderabad, in India, is one of the technological hubs of India, with a lot of business opportunities. It consists of many large companies, business houses, with large amounts of transactions happening every day, as a result of which there is an equally large amount of data generated daily. Also, India is known for many recognised universities. Learning Data Science in India will be a great opportunity for students as well as professionals. Graduates freshers and employees working in organisations can leverage these opportunities to easily land a Data Science job.
Hyderabad has several large companies, Banking and Financial institutions, Insurance companies, Automobile companies, Manufacturing enterprises, as a result, Hyderabad happens to be the most sought after city when it comes to career opportunities in Data Science.
Data science includes gathering and preparing data, conducting statistical analysis, implementing machine learning algorithms, and presenting results through visualization. Each stage ensures accuracy, delivers meaningful insights, and supports reliable predictions.
Challenges in data science involve handling incomplete or messy data, ensuring privacy and security, and addressing bias in algorithms. Grasping complex models and translating insights into actionable business strategies can also be demanding.
Key locations include Ameerpet (500016), Banjara Hills (500034), Madhapur (500081), Kukatpally (500072), HiTech City (500081), Gachibowli (500032), Begumpet (500016), Somajiguda (500082), Sanjeeva Reddy Nagar (500038), Kondapur (500084), Malkajgiri (500047), Madhura Nagar (500038), Nallakunta (500044), Tarnaka (500017), Secunderabad (500003), Himayatnagar (500029), Malakpet (500036), Amberpet (500013), Boduppal (500039), KPHB Colony (500072), Vasundhara Nagar (500062), LB Nagar (500074). These areas are well connected and home to many training institutes, making them convenient for students and professionals alike.
Commonly used tools and technologies in data science include Python, R, SQL, and Excel for data management, along with Tableau and Power BI for visualization. Libraries like scikit-learn and cloud platforms are also widely used for analysis and deployment.
Yes, graduates from any discipline in Hyderabad can enroll. Strong analytical skills and basic programming knowledge are important, and pursuing additional courses or certifications in the city can help bridge any skill gaps.
The duration of the Data Science course in Hyderabad typically ranges from 8 to 12 months, depending on the learning pace and schedule chosen by the student. Training sessions are available on both weekdays and weekends, allowing learners to select a flexible option that suits their convenience.
Hyderabad is one of India’s fastest-growing IT hubs, with increasing adoption of AI, machine learning, and data-driven decision-making across industries such as IT services, healthcare, fintech, and e-commerce. This rapid digital transformation has created strong demand for skilled data science professionals, making it a highly promising location to start a data science career in Hyderabad.
The Data Science course fee in Hyderabad generally ranges from INR 15,000 to INR 2,50,000, depending on the course type, duration, and training mode selected. Fees may vary based on whether learners choose beginner-level programs, advanced certifications, or specialized data science tracks, along with options such as online, classroom, or blended learning.
After completing the Certified Data Scientist course in Hyderabad, learners will be well-equipped with the following key objectives:
Gain a strong understanding of the complete data science project lifecycle, from data collection to model deployment.
Build a solid foundation in statistics and its practical applications in data science.
Learn and apply various machine learning algorithms for predictive and analytical tasks.
Develop skills in data forecasting, data mining, and data visualization techniques.
Understand how to deliver end-to-end data science projects with real-world implementation experience.
As per Glassdoor, the salary of a Data Scientist in Hyderabad typically ranges from ₹5–8 LPA for entry-level professionals and can go up to ₹15–25 LPA for experienced candidates, depending on skills, experience, and the hiring company. With strong demand in AI, machine learning, and data analytics, compensation continues to grow for skilled professionals.
DataMites Hyderabad welcomes professionals, fresh graduates, and career switchers. A basic understanding of mathematics and programming is generally sufficient, though prerequisites may vary depending on the course level and focus.
DataMites Hyderabad offers structured learning, expert trainers, and placement support. Its curriculum is designed around industry-relevant skills and tools, making it an excellent choice for anyone looking to build a career in data science with proper guidance and a clear learning path.
The DataMites Data Science course fee in Hyderabad varies depending on the chosen learning mode. The live virtual program is priced at INR 60,000, the blended learning option costs INR 35,000, and classroom training is available for INR 65,000. For the latest and most accurate fee details, it is recommended to contact the Hyderabad center directly.
DataMites Hyderabad offers a full refund if cancellation is requested within one week of the course start, provided that at least two sessions have been attended. Refunds are typically processed within 5–7 business days and are not available after six months from the enrollment date.
Yes, DataMites Hyderabad offers a data science course with internships. Learners gain practical experience through real-world projects, enhancing their skills and improving career prospects.
You have access to the online study materials from 6 months upto 1 year.
The DataMites data science course in Hyderabad spans 8 months, totaling around 700 learning hours. It is structured to balance theoretical knowledge with practical, hands-on training, covering all essential aspects of data science.
Yes, DataMites Hyderabad provides certification upon successful completion of the Data Science program. The certification is issued by recognized organizations such as IABAC® and NASSCOM® FutureSkills, validating your skills and boosting career opportunities in the data science field.
The DataMites Data Science syllabus includes core topics such as statistics, Python or R programming, machine learning, data visualization, and data mining. Many programs also cover big data technologies, AI frameworks, and practical projects, ensuring learners gain both theoretical knowledge and hands-on experience.
Yes, DataMites Hyderabad provides a free demo class for its data science courses. This allows prospective students to explore the course structure and teaching approach before enrolling, helping them make an informed decision about their learning journey.
Yes. At DataMites Hyderabad, students engage in live projects, gaining exposure to real-world challenges and solutions. This practical experience bridges the gap between classroom learning and industry expectations, effectively preparing them for careers in data science.
DataMites Hyderabad offers both live and recorded online classes for its data science courses. Live sessions enable real-time interaction with instructors, while recorded sessions allow students to revisit the material at their convenience. This combination provides a flexible and comprehensive learning experience.
A Certified Data Scientist course provides structured training in essential data science concepts and techniques. It typically covers programming, statistics, machine learning, and data visualization. Earning this certification validates your expertise and enhances career prospects in the field of data science.
DataMites is a training provider that imparts quality training and upskilling in Data Science, for freshers who are data enthusiasts and professionals who wish to enhance their career possibilities. Above all DataMites offers the following;-
Industry aligned courses
Online sessions that ensure good engagement.
Expert Trainers, who possess a vast knowledge of the subject matter.
Case studies approach, which delved deep into the practical application of the concepts.
Opportunity to get connected with a network of Data Science professionals.
Career Guidance
Opportunity to work on projects
DataMites provides Flexi Pass, which gives you the privilege to attend unlimited batches in a year. The flexi pass is specific to one particular course. Therefore if you have a flexi pass for one particular course of your choice, you will be able to attend any number of sessions of that course. It is to be noted that a flexi pass is valid for a particular period.
The trainers at DataMites Hyderabad are experienced industry professionals with strong expertise in data science. They provide thorough instruction and personalized mentorship to guide each student throughout their learning journey.
All the online sessions are recorded and will be shared with the candidates. If you miss any of the online sessions, you can still have access to the recordings later.
Students from different parts of Hyderabad can conveniently access the DataMites Hyderabad center, located at 313, 4th Floor, Ayyappa Society Main Rd, Ayyappa Society, Megha Hills, Madhapur, Hyderabad, Telangana 500081. The center is well connected to nearby areas such as Ameerpet (500016), Banjara Hills (500034), Madhapur (500081), Kukatpally (500072), HiTech City (500081), Gachibowli (500032), Begumpet (500016), Somajiguda (500082), Sanjeeva Reddy Nagar (500038), Kondapur (500084), Malkajgiri (500047), Madhura Nagar (500038), Nallakunta (500044), Tarnaka (500017), Secunderabad (500003), Himayatnagar (500029), Malakpet (500036), Amberpet (500013), Boduppal (500039), KPHB Colony (500072), Vasundhara Nagar (500062), LB Nagar (500074). This makes it convenient for learners from residential, commercial, and educational hubs to attend offline DataMites courses with practical, hands-on training.
DataMites provides multiple payment options, including debit/credit cards (Visa, MasterCard, American Express) and PayPal. After payment, students receive course materials and enrollment confirmation, with an educational counselor available to assist them throughout the process.
DataMites Hyderabad offers both online and offline data science courses, allowing students to choose the mode that best fits their schedule and learning style. The curriculum and teaching quality remain consistent across both formats. The Hyderabad center is located at 313, 4th Floor, Ayyappa Society Main Rd, Megha Hills, Madhapur, Hyderabad, Telangana 500081.
Yes, DataMites provides EMI options for the data science courses in Hyderabad, allowing learners to pay the course fee in flexible monthly installments. This makes the training more affordable and accessible for students and working professionals.
DataMites Madhapur training center is conveniently located at 313, 4th Floor, Ayyappa Society Main Road, Ayyappa Society, Megha Hills, Madhapur, Hyderabad, Telangana 500081.
DataMites Kukatpally training center is situated at 4th Floor, MIG-13/14, opp. JNTU, Kukatpally Housing Board Colony, Dharma Reddy Colony Phase I, Kukatpally, Hyderabad, Telangana 500072.
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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