DATA SCIENCE CERTIFICATION AUTHORITIES

Data Science Course Features

DATA SCIENCE COURSE LEAD MENTORS

DATA SCIENCE COURSE FEE IN MARATHAHALLI, BANGALORE

Live Virtual

Instructor Led Live Online

110,000
59,451

  • IABAC® & NASSCOM® Certification
  • 8-Month | 700 Learning Hours
  • 120-Hour Live Online Training
  • 25 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Blended Learning

Self Learning + Live Mentoring

66,000
34,951

  • Self Learning + Live Mentoring
  • IABAC® & NASSCOM® Certification
  • 1 Year Access To Elearning
  • 25 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Leaner assistance and support

Classroom

In - Person Classroom Training

110,000
64,451

  • IABAC® & NASSCOM® Certification
  • 8-Month | 700 Learning Hours
  • 120-Hour Classroom Sessions
  • 25 Capstone & 1 Client Project
  • Cloud Lab Access
  • Internship + Job Assistance

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UPCOMING DATA SCIENCE ONLINE CLASSES IN MARATHAHALLI

UPCOMING DATA SCIENCE OFFLINE CLASSES IN MARATHAHALLI

BEST DATA SCIENCE CERTIFICATIONS

The entire training includes real-world projects and highly valuable case studies.

IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.

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WHY DATAMITES FOR DATA SCIENCE TRAINING

Why DataMites Infographic

SYLLABUS OF DATA SCIENCE CERTIFICATION COURSE

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

OFFERED DATA SCIENCE COURSES IN MARATHAHALLI

DATA SCIENCE TRAINING COURSE REVIEWS

ABOUT DATA SCIENCE COURSE IN MARATHAHALLI

DataMites Institute, a globally recognized leader in data science training in Marathahalli, offers advanced programs designed to cater to the dynamic demands of aspiring data professionals. With a focus on hands-on learning, real-world projects, and comprehensive career support, DataMites has established itself as the trusted choice for data science courses in Bangalore. Strategically located in Marathahalli, one of Bangalore’s most vibrant neighborhoods, our online data science course in Marathahalli offers seamless accessibility for learners from nearby areas, including Kundalahalli, Whitefield, HAL, Mahadevapura Bellandur, and Brookefield.

Our Certified Data Scientist Course is an 8-month, IABAC and NASSCOM FutureSkills accredited program designed to meet global industry standards. The comprehensive training combines classroom sessions, live projects, and internships, offering students real-world exposure. With a focus on practical learning and robust career support, our data science course in Marathahalli with placements ensures learners are fully equipped to excel in the job market.

This course covers essential topics, including Python programming, machine learning, data visualization, and artificial intelligence. By the end of the program, students gain a strong foundation in data science, preparing them for roles such as Data Scientist, Machine Learning Engineer, Data Analyst, and Business Intelligence Analyst.

Data Science Training in Marathahalli: Unleash Your Potential

Bangalore, known as the "Silicon Valley of India," stands as a premier tech hub. Marathahalli, with its excellent infrastructure and close proximity to top IT giants like Infosys, Wipro, TCS, and Accenture, is the perfect destination for aspiring data scientists. Nestled among leading tech firms and startups, this area offers exceptional exposure to the thriving tech ecosystem. As the demand for data-driven solutions grows across industries, data science professionals have immense career opportunities. Enrolling in a data science course in Bangalore equips you with the foundation needed to leverage these opportunities and succeed in the field.

As reported by Grand View Research, the global data science platform market was valued at USD 96.25 billion in 2023 and is projected to grow at a CAGR of 26.0% from 2024 to 2030. This remarkable growth underscores the increasing reliance on data-driven insights, further amplifying the demand for skilled data science professionals in Bangalore.

Why Choose Marathahalli for Your Data Science Training?

Marathahalli is a prime location for data science training in Bangalore, particularly with DataMites Training Institute situated in this vibrant area. Several key factors make Marathahalli an excellent choice:

1. Expanding Technology Hub: Positioned at the intersection of key tech hubs such as Whitefield, HAL, and Bellandur, Marathahalli offers excellent access to major IT companies and startups, making it easily accessible for professionals and students alike.

2. Technology-Driven Community: Marathahalli is surrounded by renowned tech parks, businesses, and startups that leverage data-driven solutions, creating ample opportunities for data science courses in Marthahalli with internship and placements, particularly for students attending DataMites Institute in Marathahalli.

3. Cost-Effective Lifestyle: Compared to other tech hubs in Bangalore, Marathahalli offers a relatively affordable cost of living, allowing students to focus on their studies without financial strain.

4. Vibrant Community: Marathahalli is known for its educational institutions and lively atmosphere, providing a collaborative learning environment. It also offers access to a strong network of professionals, enriching the experience for those enrolled at DataMites Training Institute in Marathahalli.

Why Choose DataMites in Marathahalli for Data Science Training?

DataMites offers an all-encompassing data science certification course in Marathahalli, combining global standards with practical, hands-on learning experiences.

1. Globally Recognized Certifications: Our courses are accredited by IABAC and NASSCOM FutureSkills, ensuring your certification is industry-recognized worldwide.

2. Expert Faculty: Learn from experienced trainers with deep industry expertise.

3. Flexible Learning Options: Choose between online or offline data science course in Marathahalli, our state-of-the-art center in Marathahalli.

4. Hands-On Experience: Work on 20 capstone projects and one client project to gain real-world problem-solving experience.

5. Placement Assistance: With a dedicated Placement Assistance Team, we provide resume building, interview preparation, and job placement support to ensure you achieve your career goals.

DataMites 3-Phase Learning Methodology

To provide a thorough and effective learning experience, DataMites follows a structured 3-phase approach:

Phase 1:Pre-Course Study:
Students kickstart their learning journey with video tutorials and self-study materials, establishing a strong understanding of data science fundamentals before attending the classroom sessions.

Phase 2: Immersive Training
This phase includes 20 hours of weekly training over the span of three months. Students have the option to attend live online sessions or offline data science classes in Bangalore. The curriculum is designed to provide hands-on experience with real-world projects, guided by industry experts.

Phase 3: Internship & Placement
In this final phase, students complete 20 capstone projects and one client-based project, gaining valuable practical experience. They also earn an internship certification. The DataMites Placement Assistance Team provides job support, helping students secure roles in leading tech companies.

Explore Specialized Data Science Certifications in Marathahalli

DataMites also offers domain-specific certifications, such as:

1. Data Science for Managers: This course is aimed at executives and senior leaders, providing them with the tools and knowledge to integrate data-driven insights into high-level decision-making processes.

2. Python for Data Science: A beginner-friendly program designed to introduce Python programming, focusing on its role and applications in data science tasks.

3. Domain-Specific Data Science: This series of specialized programs explores how data science is applied in specific industries, such as human resources, finance, and marketing.

4. Diploma in Data Science: This advanced course offers a deeper dive into data science, ideal for professionals seeking to build expertise and advance in data-driven roles.

Start Your Data Science Journey at DataMites Marathahalli

Kickstart your career in data science with our data science course in Bangalore at our Marathahalli center, where you’ll gain access to expert training, hands-on projects, and a growing tech community. Our offline data science classes in Marathahalli are specifically designed to meet the needs of aspiring professionals, ensuring a seamless pathway to a successful career. DataMites also offers specialized courses in Data Analytics, Artificial Intelligence, Machine Learning, Python, and the Certified Data Scientist Course.

Visit the DataMites Marathahalli center, located at 1st Floor, 761/1, Outer Ring Rd, near KLM Mall, Marathahalli Village, Marathahalli, Bengaluru, Karnataka 560037, to begin your journey and transform your career with data science. Join us today and unlock the potential of your future in data science!

ABOUT DATAMITES DATA SCIENCE COURSE IN MARATHAHALLI

To study data science in Marathahalli, explore local training institutes or online platforms. DataMites provides a well-structured curriculum with hands-on projects to develop skills effectively. They also offer offline classes in nearby areas like BTM Layout and Kudlu Gate.

The Data Science syllabus at Marathahalli encompasses essential topics like Python programming, data analysis, and machine learning. It features modules on data visualization, statistical techniques, and real-world projects, focusing on equipping learners with practical skills and hands-on experience in data science.

DataMites in Marathahalli offers a comprehensive Data Science course covering Python, statistics, machine learning, and Tableau. Accredited by IABAC and NASSCOM FutureSkills, it ensures industry recognition with flexible learning options.

Data science courses in Marathahalli generally range from 4 to 12 months, depending on the type of program. The duration may vary based on whether the course is full-time or part-time, online or offline. It is recommended to check the course details for more accurate information.

Yes, offline data science courses are available at the DataMites Marathahalli branch located at 1st Floor, 761/1, Outer Ring Rd, near KLM Mall, Marathahalli Village, Marathahalli, Bengaluru, Karnataka 560037. Individuals from nearby areas like Kundalahalli (560037), Whitefield (560066), HAL (560008), Mahadevapura (560048), Bellandur (560103), and Brookefield (560066) can also enroll in these courses. The center provides hands-on training in a professional environment, perfect for those looking to gain practical experience.

DataMites Institute in Marathahalli is a highly regarded center for data science education, providing in-depth training in essential fields such as machine learning, AI, and data analysis. The curriculum is tailored to industry requirements, equipping students with valuable, real-world skills. With expert trainers and practical projects, DataMites is a top choice for those pursuing a career in data science.

The Data Science course in Marathahalli can be suitable for freshers if it covers fundamental concepts and hands-on experience. It is important to evaluate the course content, faculty expertise, and student reviews. Choosing a program that offers strong support and practical exposure would be beneficial for beginners.

In Bangalore, Data Scientists can earn between ₹4 Lakhs and ₹36 Lakhs annually, with the average salary being around ₹15 Lakhs. Salaries can differ based on factors like experience, skill set, and the employer. Entry-level positions generally offer salaries on the lower end of this spectrum.

Individuals with logical, mathematical, and analytical skills are eligible for the Data Science course at the Marathahalli branch. This includes professionals from various domains, statisticians, economists, mathematicians, software programmers, business analysts, Six Sigma consultants, and freshers with strong analytical abilities.

Coding proficiency is highly beneficial for a career in data science, as it enables effective data manipulation and analysis. While not always required, knowledge of programming languages like Python or R is often essential for tasks such as data cleaning and modeling. Additionally, coding skills improve the ability to automate and optimize processes in data-driven environments.

To pursue a career in data science, a strong foundation in mathematics, statistics, and programming is essential. A degree in fields like computer science, engineering, or data science is commonly preferred. Practical experience with data analysis tools and machine learning techniques is also highly valuable.

Bangalore remains a key hub for data science, with a growing demand for skilled professionals across industries like IT, finance, and healthcare. The city's strong tech ecosystem and numerous startups continue to fuel this demand. As data-driven decision-making expands, the outlook for data science roles is expected to stay positive and evolve with emerging technologies.

Yes, learning Python is highly recommended for data science students. It is a versatile language with a rich ecosystem of libraries like NumPy, pandas, and scikit-learn, essential for data analysis and machine learning. Python's simplicity and widespread use make it an ideal tool for aspiring data scientists.

Essential skills for a career in data science include strong proficiency in programming languages like Python or R, statistical analysis, and data manipulation. A solid understanding of machine learning algorithms and data visualization techniques is also crucial. Effective problem-solving and communication skills are key to translating data insights into actionable business strategies.

A data scientist is a professional who analyzes and interprets complex data to help organizations make informed decisions. They use statistical methods, machine learning, and programming skills to extract insights. Their role includes data collection, cleaning, modeling, and visualizing results.

Mastering data science can be challenging due to its broad scope, requiring knowledge in statistics, programming, and domain expertise. Continuous learning is necessary as the field evolves with new tools and techniques. Success depends on persistence, practical experience, and a strong foundation in core concepts.

Common tools used in data science include programming languages like Python and R for data analysis and modeling. Data visualization tools like Tableau and Power BI help in presenting insights. Additionally, libraries such as TensorFlow and scikit-learn are widely used for machine learning tasks.

Yes, data science roles remain in high demand in Bangalore.

  • Bangalore is a leading technology hub in India with a strong presence of IT and data-driven companies.
  • A report by LinkedIn in 2023 showed Bangalore ranking high in terms of job openings for data science professionals.

Data Science is crucial today due to its ability to extract valuable insights from massive datasets. This enables businesses to make data-driven decisions, improve operations, and gain a competitive edge. Furthermore, it plays a vital role in addressing complex challenges across various fields, such as healthcare, finance, and environmental science.

A Data Scientist focuses on building models, algorithms, and predictive analytics using advanced statistical and machine learning techniques. A Data Analyst, on the other hand, primarily works with data visualization, reporting, and descriptive analysis to inform business decisions. The key difference lies in the complexity and scope of tasks they handle.

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FAQ'S OF DATA SCIENCE TRAINING IN MARATHAHALLI

DataMites offers internship opportunities alongside their Data Science course in Marathahalli. These internships provide practical experience to enhance your learning. For more information, you can visit their website or get in touch with their support team.

In Bangalore, Data Science course fees generally vary from INR 15,000 to INR 2,50,000. At DataMites' Marathahalli branch, fees for different courses range from INR 40,000 to INR 1,20,000. The Certified Data Scientist Program, an 8-month course, is priced at INR 59,451 for online, INR 64,451 for offline, and INR 34,951 for blended learning. Other offerings like the Data Science Foundation and Data Science for Managers start at INR 24,000.

Yes, DataMites offers EMI options for their Data Science courses in Marathahalli. This allows students to pay the course fees in convenient monthly installments. You can inquire directly with the DataMites support team for further details on the EMI plans available.

To enroll in the DataMites Data Science course, visit our website and choose the course you wish to pursue. Complete the registration form and proceed with payment via debit/credit card or PayPal. After payment, you will receive your course materials, schedule, and receipt. For assistance, feel free to contact our educational counselor.

When you enroll in the Data Science course in Marathahalli, you'll receive comprehensive learning materials, including course books, online resources, and practice datasets. You'll also have access to recorded lectures, real-world projects, and dedicated support throughout the course. Additionally, you'll be provided with guidance on industry tools and techniques.

Yes, DataMites Marathahalli offers Data Science courses that include live projects. These courses are designed to provide practical experience, enhancing your learning. For more details, you can visit our official website. 

Upon completing the Data Science course at DataMites, you will receive recognized certifications. These include the IABAC® certification, globally acknowledged, and the NASSCOM FutureSkills certification. Both demonstrate your proficiency in data science.

The DataMites branch in Marathahalli is situated at:

1st Floor, 761/1, Outer Ring Rd, close to KLM Mall, Marathahalli Village, Marathahalli, Bengaluru, Karnataka 560037.

People from nearby locations such as Kundalahalli (560037), Whitefield (560066), HAL (560008), Mahadevapura (560048), Bellandur (560103), and Brookefield (560066) are also eligible to enroll in these courses.

The trainers at DataMites Institute are seasoned professionals with deep expertise in data science, Python programming, and AI. They bring valuable industry insights and hands-on experience to enrich the learning process. Committed to delivering thorough guidance, DataMites trainers ensure a strong grasp of the course material.

Yes, DataMites in Marathahalli offers free data science demo sessions. These sessions are available both online and offline, with flexible scheduling on weekdays and weekends. For more details or to register, please contact your education counselor.

DataMites offers a 100% refund if you request it 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 course material has been accessed. To request a refund, email care@datamites.com from your registered email.

DataMites has three offline training centers in Bangalore:

  • Kudlu Gate: Nestled in a fast-growing tech hub, this center provides a modern, well-equipped environment for data science learning.

  • Marathahalli: Positioned in a key tech zone, it offers top-notch courses to professionals and students, with proximity to major IT parks like RMZ Ecospace.

  • BTM Layout: Located in South Bangalore, this center offers easy access to extensive data science training for learners in the region.

DataMites in Marathahalli provides Data Science training with internationally recognized certifications, ensuring a high standard of education. Courses are taught by industry professionals, offering practical insights and opportunities for internships and job placements. With flexible schedules, the program caters to various learning needs, making it an ideal option for those looking to advance in data science.

Yes, DataMites Marathahalli offers data science courses with placement assistance. They provide comprehensive training in data science, machine learning, and related fields. The institute also offers placement assistance to help students secure job opportunities.

Yes, if you miss a class, you can make up for it by reviewing the recorded session. All online sessions are recorded and will be shared with the candidates. You can access the recordings at your convenience.

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: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

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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