DATA ANALYST CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYST LEAD MENTORS

DATA ANALYST COURSE FEE IN RWANDA

Live Virtual

Instructor Led Live Online

RF 1,523,080
RF 864,310

  • IABAC® Certification
  • 6-Month | 200+ Learning Hours
  • 20 HOURS LEARNING A WEEK
  • 10 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Blended Learning

Self Learning + Live Mentoring

RF 761,540
RF 495,310

  • Self Learning + Live Mentoring
  • IABAC® Certification
  • 1 Year Access To Elearning
  • 10 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Learner 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

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UPCOMING DATA ANALYST ONLINE CLASSES IN RWANDA

BEST DATA ANALYTICS 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 INSTITUTE FOR DATA ANALYST COURSE

Why DataMites Infographic

SYLLABUS OF DATA ANALYST COURSE IN RWANDA

MODULE 1: DATA ANALYSIS FOUNDATION

• Data Analysis Introduction
• Data Preparation for Analysis
• Common Data Problems
• Various Tools for Data Analysis
• Evolution of Analytics domain

MODULE 2: CLASSIFICATION OF ANALYTICS

• Four types of the Analytics
• Descriptive Analytics
• Diagnostics Analytics
• Predictive Analytics
• Prescriptive Analytics
• Human Input in Various type of Analytics

MODULE 3: CRIP-DM Model

• Introduction to CRIP-DM Model
• Business Understanding
• Data Understanding
• Data Preparation
Modeling, Evaluation, Deploying,Monitoring

MODULE 4: UNIVARIATE DATA ANALYSIS

• Summary statistics -Determines the value’s center and spread.
• Measure of Central Tendencies: Mean, Median and Mode
• Measures of Variability: Range, Interquartile range, Variance and Standard Deviation
• Frequency table -This shows how frequently various values occur.
• Charts -A visual representation of the distribution of values.

MODULE 5: DATA ANALYSIS WITH VISUAL CHARTS

• Line Chart
• Column/Bar Chart
• Waterfall Chart
• Tree Map Chart
• Box Plot

MODULE 6: BI-VARIATE DATA ANALYSIS

• Scatter Plots
• Regression Analysis
• Correlation Coefficients

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
  • Empherical Rule  and Outliers
  • Central Limit Theorem
  • Normality Testing
  • Skewness & Kurtosis
  • Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance
  • 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: COMPARISION AND CORRELATION ANALYSIS

• Data comparison Introduction,
• Performing Comparison Analysis on Data
• Concept of Correlation
• Calculating Correlation with Excel
• Comparison vs Correlation
• Hands-on case study : Comparison Analysis
• Hands-on case study Correlation Analysis

MODULE 2: VARIANCE AND FREQUENCY ANALYSIS

• Variance Analysis Introduction
• Data Preparation for Variance Analysis
• Performing Variance and Frequency Analysis
• Business use cases for Variance Analysis
• Business use cases for Frequency Analysis

MODULE 3: RANKING ANALYSIS

• Introduction to Ranking Analysis
• Data Preparation for Ranking Analysis
• Performing Ranking Analysis with Excel
• Insights for Ranking Analysis
• Hands-on Case Study: Ranking Analysis

MODULE 4: BREAK EVEN ANALYSIS

• Concept of Breakeven Analysis
• Make or Buy Decision with Break Even
• Preparing Data for Breakeven Analysis
• Hands-on Case Study: Manufacturing

MODULE 5: PARETO (80/20 RULE) ANALSYSIS

• Pareto rule Introduction
• Preparation Data for Pareto Analysis,
• Performing Pareto Analysis on Data
• Insights on Optimizing Operations with Pareto Analysis
• Hands-on case study: Pareto Analysis

MODULE 6: Time Series and Trend Analysis

• Introduction to Time Series Data
• Preparing data for Time Series Analysis
• Types of Trends
• Trend Analysis of the Data with Excel
• Insights from Trend Analysis

MODULE 7: DATA ANALYSIS BUSINESS REPORTING

• Management Information System Introduction
• Various Data Reporting formats
• Creating Data Analysis reports as per the requirements

MODULE 1: DATA ANALYTICS FOUNDATION

• Business Analytics Overview
• Application of Business Analytics
• Benefits of Business Analytics
• Challenges
• Data Sources
• Data Reliability and Validity

MODULE 2: OPTIMIZATION MODELS

• Predictive Analytics with Low Uncertainty;Case Study
• Mathematical Modeling and Decision Modeling
• Product Pricing with Prescriptive Modeling
• Assignment 1 : KERC Inc, Optimum Manufacturing Quantity

MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION

• Mathematics behind Linear Regression
• Case Study : Sales Promotion Decision with Regression Analysis
• Hands on Regression Modeling in Excel

MODULE 4: DECISION MODELING

• Predictive Analytics with High Uncertainty
• Case Study-Monte Carlo Simulation
• Comparing Decisions in Uncertain Settings
• Trees for Decision Modeling
• Case Study : Supplier Decision Modeling - Kickathlon Sports Retailer

MODULE 1: MACHINE LEARNING INTRODUCTION

• What Is ML? ML Vs AI
• ML Workflow, Popular ML Algorithms
• Clustering, Classification And Regression
• Supervised Vs Unsupervised

MODULE 2: ML ALGO: LINEAR REGRESSSION

• Introduction to Linear Regression
• How it works: Regression and Best Fit Line
• Hands-on Linear Regression with ML Tool

MODULE 3: ML ALGO: LOGISTIC REGRESSION

• Introduction to Logistic Regression;
• Classification & Sigmoid Curve
• Hands-on Logistics Regression with ML Tool

MODULE 4: ML ALGO: KNN

• Introduction to KNN; Nearest Neighbor
• Regression with KNN
• Hands-on: KNN with ML Tool

MODULE 5: ML ALGO: K MEANS CLUSTERING

• Understanding Clustering (Unsupervised)
• Introduction to KMeans and How it works
• Hands-on: K Means Clustering

MODULE 6: ML ALGO: DECISION TREE

• Decision Tree and How it works
• Hands-on: Decision Tree with ML Tool

MODULE 7: ML ALGO: SUPPORT VECTOR MACHINE (SVM)

• Introduction to SVM
• How It Works: SVM Concept, Kernel Trick
• Hands-on: SVM with ML Tool

MODULE 8: ARTIFICIAL NEURAL NETWORK (ANN)

• Introduction to ANN, How It Works
• Back propagation, Gradient Descent
• Hands-on: ANN with ML Tool

MODULE 1: DATABASE INTRODUCTION

• DATABASE Overview
• Key concepts of database management
• CRUD Operations
• Relational Database Management System
• RDBMS vs No-SQL (Document DB)

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 Functions: 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
• MongoDB data management

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 ANALYST COURSES IN RWANDA

DATA ANALYST COURSE REVIEWS

ABOUT DATA ANALYST TRAINING IN RWANDA

In the ever-evolving domain of Data Analytics, the sector is poised for remarkable growth, with a projected Compound Annual Growth Rate (CAGR) of 26.8%. As per KBV Research, the Global Data Analytics Market is forecasted to reach an impressive size of $301.8 billion by 2030. This surge underscores the escalating reliance on data-driven insights across various industries, underscoring the pivotal role of analytics in shaping the future.

For those seeking to navigate the burgeoning field of Data Analytics, consider DataMites—an eminent global training institute. Specializing in equipping individuals with the skills required to thrive in this dynamic industry, DataMites offers a Certified Data Analyst Course in Rwanda. This comprehensive program, tailored for beginners and intermediate learners, covers essential aspects such as Data Analysis, Data Science Foundation, Statistics, Visual Analytics, Data Modeling, and Predictive Modeling. Successful completion of the course culminates in an IABAC Certification, enhancing credibility in the competitive analytics landscape.

At DataMites, our Certified Data Analyst Training in Rwanda unfolds in three comprehensive phases to ensure a thorough understanding and practical application of Data Analytics concepts.

Phase 1: Pre Course Self-Study

Initiate your learning journey with high-quality videos employing an easy learning approach, allowing you to delve into the fundamentals at your own pace.

Phase 2: 3-Month Duration

Experience live training sessions spanning 20 hours a week over three months. Our comprehensive syllabus covers key areas, supported by hands-on projects. Engage with expert trainers and mentors who guide you through this intensive phase.

Phase 3: 3-Month Duration

Cap off your training with project mentoring, involving five or more capstone projects. Immerse yourself in real-time internship opportunities, culminating in a client/live project. Achieve certification from both IABAC and the data analytics internship in Rwanda, solidifying your expertise.

Certified Data Analyst Courses in Rwanda - Features

  1. Global Perspective: At DataMites, excellence in education is personified through our lead mentor, Ashok Veda, a luminary with over 19 years of experience in Data Analytics and AI. As the Founder & CEO at Rubixe™, his leadership ensures a cutting-edge curriculum and top-tier learning experience.
  2. No-Code Program (Optional Python): Tailor your learning experience to your comfort with a no-code program, optionally incorporating Python.
  3. Duration: Immerse yourself in a 6-month program, committing 20 hours a week for a total of 200+ learning hours.
  4. Global Certification: Attain recognition with the esteemed IABAC® Certification.
  5. Flexibility: Enjoy the convenience of flexible learning through online data analytics courses in Rwanda and self-study modules.
  6. Real-World Projects: Apply your skills through 5+ capstone projects and a client/live project during an enriching data analytics courses with internship in Rwanda.
  7. End-to-End Job Support: Benefit from comprehensive career guidance, personalized resume building, and data analytics interview preparation.
  8. DataMites Exclusive Learning Community: Join a vibrant community, fostering collaborative learning and networking.
  9. Affordable Pricing and Scholarships: Our commitment to accessibility is reflected in our affordable pricing, with data analytics course fees in Rwanda ranging from RWF 543,254 to RWF 1,670,477. Explore scholarship opportunities to further enhance affordability.

Rwanda's Data Analytics sector is rapidly evolving, reflecting the nation's commitment to technological advancement. As industries embrace data-driven strategies, the demand for Data Analysts is witnessing significant growth, positioning Rwanda as a hub for analytics excellence.

In Rwanda, the role of a Data Analyst commands substantial recognition and reward. Glassdoor reveals an average annual data analyst salary in Rwanda of 8,560,000 RWF, affirming the industry's acknowledgment of the pivotal role Data Analysts play in driving success. This competitive salary underscores the high value placed on analytical expertise in Rwanda, making it an attractive destination for professionals seeking both meaningful work and substantial financial rewards in the Data Analytics field.

As Rwanda steers towards technological prominence, DataMites offers a gateway to career success. Explore our array of courses apart from data analytics training in Rwanda, including Artificial Intelligence, Machine Learning, Data Engineering, Data Science, Tableau, Python, and beyond. With a commitment to quality education, DataMites is your definitive choice for mastering the skills needed for success in Rwanda's burgeoning tech industry.

ABOUT DATAMITES DATA ANALYST COURSE IN RWANDA

Data analytics involves deriving insights from raw data to drive decision-making and streamline processes, employing statistical analysis, machine learning, and data visualization techniques.

Data analysts typically engage in tasks such as gathering and cleansing data, conducting statistical analysis, creating data visualizations, and producing reports to extract insights and guide decision-making processes.

Projects provide invaluable hands-on experience, enabling learners to apply theoretical concepts to real-world data, fostering critical thinking, problem-solving skills, and reinforcing understanding through practical application.

Absolutely, there's a substantial demand for data analytics jobs across industries, fueled by the exponential growth and complexity of generated data.

Primary roles in data analytics careers include data analyst, data scientist, business intelligence analyst, and data engineer, each specializing in different facets of data management and analysis.

The future of data analysis looks promising, propelled by advancements in artificial intelligence, machine learning, and big data technologies, leading to more sophisticated analytics capabilities and increased automation.

Indeed, there is a plethora of consulting opportunities in Data Analytics, providing services ranging from strategizing to implementing and optimizing data-driven solutions for businesses.

Data Analytics Internships are vital as they offer practical experience, exposure to real-world datasets, and the opportunity to collaborate with professionals. They facilitate the application of theoretical knowledge, skill development, and networking essential for a successful career in Data Analytics.

Essential tools for mastering Data Analytics include programming languages like Python or R, statistical software such as Excel or SPSS, data visualization tools like Tableau or Power BI, and database management systems like SQL.

Essential skills for data analytics encompass proficiency in programming, statistical analysis, data visualization, critical thinking, and domain expertise.

Proficiency in Data Analytics within six months is feasible through focused study, practice, and hands-on projects, though achieving mastery may necessitate longer-term dedication and practical experience.

According to Glassdoor, the average annual salary for data analysts in Rwanda is 8,560,000 RWF.

DataMites offers exceptional data analytics training in Rwanda, covering statistical techniques, machine learning, and data visualization. Through hands-on projects and expert instructors, DataMites prepares students for successful careers in data analytics.

Machine learning intersects with data analytics by employing algorithms and statistical models to analyze data, identify patterns, and make predictions or classifications. This enhances decision-making processes and automates tasks based on data-driven insights.

While data analytics may involve coding, the level of proficiency required varies. Basic coding skills in languages like Python or R are often necessary for data manipulation, analysis, and visualization, but the extent of coding depends on the specific job requirements.

Prerequisites for a data analyst training typically include a bachelor's degree in a relevant field like computer science, mathematics, statistics, or economics, along with proficiency in programming and statistical analysis.

Predictive analytics is applied by using historical data to develop models and algorithms that forecast future trends, behaviors, or events. This enables organizations to anticipate outcomes, make proactive decisions, and optimize strategies for better results.

Data analytics contributes to business growth by providing actionable insights derived from data analysis. This helps organizations identify growth opportunities, streamline processes, and make informed decisions that foster innovation and enhance competitiveness.

Data analytics is employed in risk management by analyzing historical data to identify patterns or anomalies indicative of potential risks or opportunities. Predictive models are developed to anticipate and mitigate risks, enabling organizations to make informed decisions and implement effective risk mitigation strategies.

The Data Analytics course can be challenging due to its multidisciplinary nature, requiring proficiency in statistics, programming, and critical thinking skills.

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FAQ’S OF DATA ANALYST TRAINING IN RWANDA

Embark on your data analytics journey with DataMites' Certified Data Analyst Course in Rwanda, offering adaptable learning formats, a curriculum tailored for real-world applications, experienced instructors, dedicated lab access, an interactive learning community, and lifetime resource availability. Providing ample project opportunities and job placement support, DataMites ensures a comprehensive and impactful learning experience.

DataMites' Data Analyst Course in Rwanda spans 6 months, with a weekly commitment of 20 learning hours. With over 200 learning hours in total, participants receive thorough training in data analytics to excel in the industry.

DataMites' certified data analyst training in Rwanda encompasses essential tools such as Power BI, crucial for crafting interactive data dashboards and reports.

Novice and intermediate learners interested in delving into data analytics can join DataMites' Certified Data Analyst Training in Rwanda. Covering fundamental areas such as data analysis, statistics, visual analytics, and predictive modeling, the program readies participants for successful careers in the field.

DataMites' Certified Data Analyst Course in Rwanda is crafted for advanced analytics and business insights, offering a NO-CODE option for learners to explore analytics without coding prerequisites.

The pricing for DataMites' Data Analytics Course in Rwanda ranges from RWF 543,254 to RWF 1,670,477. This range caters to different financial capacities, ensuring accessibility to comprehensive data analytics training. Participants can select a pricing option that aligns with their budget while still receiving quality education in Rwanda's market.

Certainly, DataMites is dedicated to offering support for participants to grasp data analytics course topics in Rwanda. With experienced educators, interactive study resources, personalized mentorship, and a collaborative learning environment, participants receive ongoing assistance to ensure their comprehension and success in the program.

Participants enrolled in the Certified Data Analyst Training in Rwanda will delve into key areas including Data Analysis Foundation, Statistics Essentials, Data Analysis Associate, Advanced Data Analytics, Predictive Analytics with Machine Learning, Database Management incorporating SQL and MongoDB, Version Control through Git, Big Data Foundation, Python Foundation, and Certified Business Intelligence (BI) Analyst.

The Flexi Pass for DataMites' Certified Data Analyst Course in Rwanda offers participants the flexibility to structure their learning journey. With this option, learners can access course materials and attend sessions at their convenience, enabling effective management of studies alongside other commitments.

Leading the Certified Data Analyst Course in Rwanda at DataMites are Ashok Veda and esteemed mentors. With extensive expertise in Data Science and AI, instructors provide participants with invaluable insights and guidance derived from their real-world experience at prominent companies and esteemed institutes like IIMs.

In its Certified Data Analyst Course in Rwanda, DataMites adopts a methodology centered around case studies. Participants delve into real-world data sets, refining their data analysis skills through practical application. This immersive approach enhances comprehension and empowers learners to tackle intricate data challenges with confidence.

DataMites offers data analytics courses in Rwanda through various learning methods, including online data analytics training in Rwanda and self-paced learning. Participants can engage in interactive online sessions or progress through course materials independently, granting them the flexibility to learn at their own pace and convenience.

Should a participant miss a data analytics session in Rwanda, DataMites provides recorded sessions for flexible viewing. Additionally, supplementary study materials and resources are accessible to help bridge any knowledge gaps. This ensures participants remain aligned with the course curriculum even if they miss a session.

Absolutely, upon completing the Certified Data Analyst Course in Rwanda at DataMites, participants receive the esteemed IABAC Certification. This credential validates their expertise in data analytics, enhancing their professional standing and unlocking rewarding career prospects in industries prioritizing data-driven decision-making.

DataMites structures its data analytics career mentoring sessions in Rwanda to provide personalized guidance and assistance. These sessions involve individual meetings with experienced mentors who offer tailored advice, insights, and career development strategies, aiding individuals in advancing their careers in data analytics.

Indeed, DataMites' Certified Data Analyst Course in Rwanda holds significant value. It's the most comprehensive non-coding course, providing accessibility to data analytics for individuals without technical backgrounds. With a three-month internship at an AI company, an experience certificate, and the prestigious IABAC Certification, participants gain industry recognition and numerous career opportunities.

Yes, DataMites offers internship opportunities alongside the Certified Data Analyst Training in Rwanda. Learners benefit from exclusive partnerships with renowned Data Science companies, gaining practical, hands-on experience. This internship enables them to apply theoretical knowledge in real-world scenarios, mentored by DataMites experts, fostering professional growth and relevance in the industry.

Absolutely, DataMites integrates live projects into its data analyst course in Rwanda. Participants engage in 5+ capstone projects and collaborate on 1 client/live project. These practical initiatives offer firsthand experience in applying data analytics skills to real-world situations, enhancing participants' proficiency and competitiveness in the industry.

Participants must bring valid photo identification, such as a national ID card or driver's license, to the training sessions. This documentation is crucial for receiving the participation certificate and scheduling certification exams, ensuring proper identification and accountability throughout the training program.

Payment options for the Certified Data Analytics Course at DataMites in Rwanda include cash, debit card, check, credit card, EMI, PayPal, Visa, Mastercard, American Express, and net banking.

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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