DATA SCIENCE CERTIFICATION AUTHORITIES

Data Science Course Features

DATA SCIENCE LEAD MENTORS

DATA SCIENCE COURSE FEE IN BRASILIA, BRAZIL

Live Virtual

Instructor Led Live Online

BRL 8,290
BRL 5,319

  • 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

BRL 4,970
BRL 3,238

  • 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

Corporate Training

Customize Your Training


  • Instructor-Led & Self-Paced training
  • Customized Learning Options
  • Industry Expert Trainers
  • Case Study Approach
  • Enterprise Grade Learning
  • 24*7 Cloud Lab

ARE YOU LOOKING TO UPSKILL YOUR TEAM ?

Enquire Now

UPCOMING DATA SCIENCE ONLINE CLASSES IN BRASILIA

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.

images not display images not display

WHY DATAMITES INSTITUTE FOR DATA SCIENCE COURSE

Why DataMites Infographic

SYLLABUS OF DATA SCIENCE COURSE IN BRASILIA

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 BRASILIA

DATA SCIENCE COURSE REVIEWS

ABOUT DATA SCIENTIST TRAINING IN BRASILIA

The data science course in Brasília unlocks the opportunities to harness the power of data for informed decision-making and advancing your career in this rapidly evolving domain. As per a report from Precedence Research, the global market for data science platforms reached USD 112.12 billion in 2022. Predictions suggest a substantial expansion to around USD 501.03 billion by 2032, indicating an estimated compound annual growth rate (CAGR) of 16.2% from 2023 to 2032. This upward trend highlights the increasing significance of data-driven decision-making across various industries worldwide.

DataMites stands out as a globally renowned institution, dedicated to providing top-notch data science training. Designed for both beginners and intermediate learners, our Certified Data Scientist Course in Brasília features a highly acclaimed curriculum covering data science and machine learning comprehensively. Recognised as a globally acclaimed and job-ready program, this initiative offers a comprehensive curriculum with integrated IABAC Certification, enhancing participants' credentials and strategically positioning them in Brasília’s competitive data science landscape.

Embarking on data science training in Brasília involves a distinctive three-phase learning approach:

In the initial phase, Begin with a self-paced pre-course study, delving into high-quality videos and an easily digestible learning method.

Progress to interactive training sessions in the second phase, where participants navigate a comprehensive syllabus, engage in hands-on projects and receive personalized guidance from experienced trainers.

Conclude with a dynamic third phase, featuring a 4-month project mentoring period, an internship experience, completion of 20 capstone projects, and active involvement in a client/live project, culminating in the attainment of an experience certificate.

DataMites delivers thorough data science training in Brasilia, presenting a varied range of inclusive programs.

Lead Mentorship by Ashok Veda: Guided by the expertise of Ashok Veda, a distinguished data scientist, DataMites excels in mentorship, ensuring students receive top-tier education from industry leaders.

Comprehensive Course Structure: Spanning 700 learning hours over 8 months, our program features a thorough course structure providing an in-depth grasp of data science, empowering students with extensive knowledge.

Global Certifications: DataMites proudly provides globally recognized certifications from IABAC®, validating the excellence and relevance of our courses.

Practical Projects: Immerse yourself in 25 Capstone projects and 1 Client Project using real-world data, offering a unique opportunity to apply theoretical knowledge in practical scenarios.

Focus on Real-World Data: With a focus on hands-on learning through real-world data projects, DataMites ensures students gain valuable practical experience alongside theoretical knowledge.

Flexible Learning: Personalize your academic journey with the flexibility of online data science courses and self-paced modules, empowering you to progress through the curriculum at your own pace.

Exclusive DataMites Learning Community: Join the exclusive DataMites Learning Community, fostering collaboration, knowledge exchange, and networking among passionate data science enthusiasts.

Internship Opportunities: DataMites offers a data science course with internship opportunities in Brasília, allowing students to gain real-world experience and enhance their skills.

Brasília, the capital of Brazil, is renowned for its modernist architecture and urban planning, featuring iconic structures like the National Congress and Cathedral of Brasília. The city, with its distinct design, serves as a political and administrative hub, reflecting Brasília's cultural diversity and historical significance. In terms of economy, Brasília boasts a diverse economic landscape driven by government activities, service sectors, and a growing technology industry, contributing significantly to the nation's economic vitality.

The data science career scope in Brasília is rapidly expanding, with increasing demand across industries for professionals skilled in harnessing data for insights and decision-making. The country's evolving digital landscape and emphasis on technological advancements further elevate the promising opportunities for data scientists in Brasília.Furthermore, the salary of a data scientist in Brasília ranges from BRL 20,850 per year according to a Glassdoor report

DataMites offers a diverse range of courses including Artificial Intelligence, Tableau, Data Analytics, Machine Learning, Data Engineering, python, and others. Guided by industry experts, our comprehensive programs ensure the mastery of crucial skills necessary for a successful career. Enroll with DataMites, the leading institute for comprehensive data science courses in Brasília, and develop profound expertise in the field.

ABOUT DATAMITES DATA SCIENCE COURSE IN BRASILIA

Data Science encompasses the extraction of insights and knowledge from data through techniques such as statistics, machine learning, and data analysis.

The operational process of Data Science involves gathering, processing, and analyzing extensive datasets to unveil meaningful patterns and trends, empowering informed decision-making across various industries.

Data Science is practically applied in predictive modeling, machine learning, and data-driven decision-making across sectors like healthcare, finance, marketing, and more.

Vital elements of a Data Science pipeline include stages like data collection, preprocessing, exploratory data analysis, feature engineering, model training, evaluation, and deployment.

Big Data and Data Science share a close relationship, as Big Data involves handling large and complex datasets with specialized tools and techniques, aligning seamlessly with the principles of Data Science.

Data Science is utilized across industries, with applications in healthcare for predictive analytics, finance for risk assessment, and e-commerce for personalized recommendations.

To embark on a Data Science career, individuals often need a background in computer science, statistics, or related fields, along with proficiency in programming and data manipulation.

Essential skills for a Data Scientist include proficiency in programming, statistical analysis, machine learning, and effective communication.

Building a strong Data Science portfolio involves showcasing projects that demonstrate practical application of skills, innovative problem-solving, and creativity.

Industries actively recruiting Data Scientists include technology, finance, healthcare, and e-commerce sectors.

Current trends in Data Science include advancements in explainable AI, automated machine learning, and a heightened focus on data ethics.

The data science job market in Brasília in 2024 is influenced by industry demand and ongoing technological advancements.

A popular choice for data science training in Brasília is the Certified Data Scientist Course, covering essential topics like machine learning and data analysis.

Data science internships in Brasília provide valuable practical experience and networking opportunities for individuals looking to enter the field.

According to a Glassdoor report, average annual salaries for data science professionals in Brasília range from BRL 20,850.

Newcomers can realistically pursue a data science course and secure employment in Brasília by developing a strong skill set and incorporating relevant projects into their portfolios.

Brasíliaian businesses leverage data science to gain customer insights, streamline processes, and make informed strategic decisions.

In the finance sector, data science applications include fraud detection, risk assessment, and algorithmic trading.

Data science significantly contributes to e-commerce by enhancing recommendation systems, personalizing user experiences, and optimizing supply chain management.

In cybersecurity, data science plays a crucial role in identifying anomalies, detecting potential threats, and overall improving security measures.

Data science applications in manufacturing and supply chain management include demand forecasting, inventory optimization, and improving overall process efficiency.

View more

FAQ’S OF DATA SCIENCE TRAINING IN BRASILIA

The Datamites™ Certified Data Scientist course extensively delves into essential aspects of data science, encompassing programming, statistics, machine learning, and business knowledge. With a focus on Python as the primary language and optional inclusion of R for those with prior experience, the course aims to provide a well-rounded understanding. Successful completion culminates in the prestigious IABAC™ certificate, preparing individuals for success in the dynamic field of data science.

While having a statistical background can be advantageous, it is not always a compulsory requirement for those seeking a career in data science in Brasília. Emphasis is often placed on proficiency in relevant tools, programming languages, and practical problem-solving skills.

  • Diploma in Data Science
  • Certified Data Scientist
  • Data Science for Managers
  • Data Science Associate
  • Statistics for Data Science
  • Python for Data Science
  • Data Science in Foundation
  • Data Science in Marketing
  • Data Science in Operations
  • Data Science in Finance
  • Data Science in HR
  • Data Science with R

In Brasília, individuals entering the data science field have access to various foundational training courses, including Certified Data Scientist, Data Science Foundation, and Diploma in Data Science.

DataMites in Brasília offers tailored courses for professionals looking to boost their expertise. These include Statistics for Data Science, Data Science with R Programming, Python for Data Science, Data Science Associate, and specialized certifications in Operations, Marketing, HR, and Finance.

The data science course in Brasília offered by DataMites has a duration of 8 months.

Career mentoring sessions at DataMites are interactive, providing personalized guidance on resume building, interview preparation, and career strategies. These sessions offer valuable insights and tactics to enhance participants' professional journey in data science.

Upon completion, participants receive the esteemed IABAC Certification from DataMites, internationally validating their proficiency in data science concepts and applications.

To excel in data science, a solid foundation in mathematics, statistics, and programming is essential. Developing analytical skills, proficiency in languages like Python or R, and hands-on experience with tools like Hadoop or SQL databases is recommended.

  • Flexibility: Online Data Science Training in Brasília allows learners to progress at their own pace, accommodating diverse schedules.
  • Accessibility: Overcoming geographical barriers, online courses are open to anyone with an internet connection.
  • Comprehensive Curriculum: DataMites ensures an extensive syllabus covering essential data science concepts and applications.
  • Industry-Relevant Content: The training aligns with industry requirements, providing practical, job-oriented skills.
  • Experienced Instructors: Participants receive guidance from skilled instructors with substantial industry experience.
  • Interactive Learning: Online platforms include engaging elements like quizzes and forums, fostering active participation.

The data science training fee in Brasília varies from BRL 2,626 to BRL 6,565 depending on the specific program.

Certainly, DataMites integrates practical learning into the Data Scientist Course in Brasília, including over 10 capstone projects and a dedicated client/live project for hands-on experience and real-world applications.

Instructors selected for data science training at DataMites hold certifications, possess extensive industry experience, and demonstrate expertise in the subject matter.

DataMites offers flexible learning methods, including Live Online sessions and self-study, to cater to participants' preferences.

The FLEXI-PASS option in DataMites' Certified Data Scientist Course allows participants to join multiple batches, enabling them to review topics, address doubts, and solidify comprehension across various sessions for a comprehensive understanding of the course content.

Yes, participants will receive a Certificate of Completion from DataMites upon finishing the Data Science Course, validating their proficiency in data science.

Participants must bring a valid Photo ID Proof, such as a National ID card or Driving License, to obtain a Participation Certificate and schedule the certification exam as needed.

In case of a missed session in the DataMites Certified Data Scientist Course in Brasília, participants usually have the option to access recorded sessions or attend support sessions to make up for missed content and clarify doubts.

Yes, potential participants at DataMites can attend a demo class before making any payment for the Certified Data Scientist Course in Brasília to assess the teaching style, course content, and overall structure.

Yes, DataMites incorporates internships into its certified data scientist course in Brasília, providing a unique learning experience that combines theoretical knowledge with practical industry exposure, enhancing skills and job opportunities.

Upon successful completion of the Data Science training, you will be granted an internationally recognized IABAC® certification, confirming your proficiency in the field and elevating your employability on a global level.

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.

View more

DATA SCIENCE COURSE PROJECTS

DATA SCIENCE JOB INTERVIEW QUESTIONS

Global DATA SCIENCE COURSES Countries

popular career ORIENTED COURSES

DATAMITES POPULAR COURSES


HELPFUL RESOURCES - DataMites Official Blog