Instructor Led Live Online
Self Learning + Live Mentoring
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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.
MODULE 1: DATA SCIENCE COURSE INTRODUCTION
MODULE 2: DATA SCIENCE ESSENTIALS
MODULE 3: DATA SCIENCE DEMO
MODULE 4: ANALYTICS CLASSIFICATION
MODULE 5: DATA SCIENCE AND RELATED FIELDS
MODULE 6: DATA SCIENCE ROLES & WORKFLOW
MODULE 7: MACHINE LEARNING INTRODUCTION
MODULE 8: DATA SCIENCE INDUSTRY APPLICATIONS
MODULE 1: PYTHON BASICS
MODULE 2: PYTHON CONTROL STATEMENTS
MODULE 3: PYTHON DATA STRUCTURES
MODULE 4: PYTHON FUNCTIONS
MODULE 5: PYTHON NUMPY PACKAGE
MODULE 6: PYTHON PANDASPACKAGE
MODULE 1: OVERVIEW OF STATISTICS
MODULE 2: HARNESSING DATA
MODULE 3: EXPLORATORY DATA ANALYSIS
MODULE 4: HYPOTHESIS TESTING
MODULE 5: CORRELATION AND REGRESSION
MODULE 1: MACHINE LEARNING INTRODUCTION
MODULE 2: PYTHON NUMPY & PANDAS PACKAGE
MODULE 3: VISUALIZATION WITH PYTHON
MODULE 4: ML ALGO: LINEAR REGRESSION
MODULE 5: ML ALGO: KNN
MODULE 6: ML ALGO: LOGISTIC REGRESSION
MODULE 7: PRINCIPLE COMPONENT ANALYSIS (PCA)
MODULE 8: ML ALGO: K MEANS CLUSTERING
MODULE 1: MACHINE LEARNING INTRODUCTION
MODULE 2: ML ALGO: LINEAR REGRESSSION
MODULE 3: ML ALGO: LOGISTIC REGRESSION
MODULE 4: ML ALGO: KNN
MODULE 5: ML ALGO: K MEANS CLUSTERING
MODULE 6: PRINCIPLE COMPONENT ANALYSIS (PCA)
MODULE 7: ML ALGO: DECISION TREE
MODULE 8 : ML ALGO: NAÏVE BAYES
MODULE 9: GRADIENT BOOSTING, XGBOOST
MODULE 10: ML ALGO: SUPPORT VECTOR MACHINE (SVM)
MODULE 11: ARTIFICIAL NEURAL NETWORK (ANN)
MODULE 12: ADVANCED ML CONCEPTS
MODULE 1: TIME SERIES FORECASTING - ARIMA
MODULE 2: FEATURE ENGINEERING
MODULE 3: SENTIMENT ANALYSIS
MODULE 4: REGULAR EXPRESSIONS WITH PYTHON
MODULE 5: ML MODEL DEPLOYMENT WITH FLASK
MODULE 6: ADVANCED DATA ANALYSIS WITH MS EXCEL
MODULE 7: AWS CLOUD FOR DATA SCIENCE
MODULE 8: AZURE FOR DATA SCIENCE
MODULE 1: DATABASE INTRODUCTION
MODULE 2: SQL BASICS
MODULE 3: DATA TYPES AND CONSTRAINTS
MODULE 4: DATABASES AND TABLES (MySQL)
MODULE 5: SQL JOINS
MODULE 6: SQL COMMANDS AND CLAUSES
MODULE 7 : DOCUMENT DB/NO-SQL DB
MODULE 1: GIT INTRODUCTION
MODULE 2: GIT REPOSITORY and GitHub
MODULE 3: COMMITS, PULL, FETCH AND PUSH
MODULE 4: TAGGING, BRANCHING AND MERGING
MODULE 5: UNDOING CHANGES
MODULE 6: GIT WITH GITHUB AND BITBUCKET
MODULE 1: BIG DATA INTRODUCTION
MODULE 2 : HDFS AND MAP REDUCE
MODULE 3: PYSPARK FOUNDATION
MODULE 4: SPARK SQL and HADOOP HIVE
MODULE 5 : MACHINE LEARNING WITH SPARK ML
MODULE 6: KAFKA and Spark
MODULE 1: BUSINESS INTELLIGENCE INTRODUCTION
MODULE 2: BI WITH TABLEAU: INTRODUCTION
MODULE 3 : TABLEAU: CONNECTING TO DATA SOURCE
MODULE 4: TABLEAU : BUSINESS INSIGHTS
MODULE 5: DASHBOARDS, STORIES AND PAGES
MODULE 6: BI WITH POWER-BI
Data Science involves extracting valuable insights and knowledge from vast volumes of structured and unstructured data, employing various techniques, algorithms, and systems for analysis, interpretation, and presentation.
The mechanism of Data Science functions by collecting, cleaning, and analyzing data to unveil meaningful patterns and trends. It utilizes statistical models, machine learning algorithms, and data visualization techniques to make informed decisions.
Practical applications of Data Science encompass predictive analytics, fraud detection, recommendation systems, sentiment analysis, and the optimization of business processes across diverse industries.
Crucial elements of a Data Science pipeline include data collection, data cleaning, exploratory data analysis (EDA), feature engineering, model training, model evaluation, and deployment.
Commonly employed programming languages in Data Science are Python and R, recognized for their extensive libraries and frameworks facilitating data manipulation, analysis, and machine learning.
Machine learning is integral to Data Science, enabling systems to learn patterns from data and make predictions or decisions without explicit programming. It enhances the extraction of valuable insights from complex datasets.
Big Data is closely linked to Data Science as it involves handling and analyzing massive datasets that traditional data processing tools may struggle with. Data Science techniques and algorithms are often applied to extract meaningful information from Big Data.
Data Science finds application in industries such as healthcare, finance, marketing, and manufacturing to optimize operations, improve decision-making, and enhance overall business performance.
While Data Science encompasses a broader range of activities, including data cleaning, exploration, and visualization, machine learning specifically focuses on developing algorithms that enable systems to learn patterns and make predictions.
Individuals from diverse backgrounds, including IT professionals, statisticians, analysts, and business professionals, are eligible to pursue Data Science certification courses. A basic understanding of statistics and programming is beneficial for learning Data Science.
The data science job market in Port-au-Prince in 2024 is witnessing growth, with an increasing demand for skilled professionals.
Considered a premier option for data science training, the Certified Data Scientist Course in Port-au-Prince covers essential subjects like machine learning and data analysis.
Data science internships hold significant value in Port-au-Prince, providing practical experience and enhancing employability.
Certainly, a newcomer can enroll in a data science course and secure a job in Port-au-Prince, as companies are open to hiring skilled beginners.
A postgraduate degree is not mandatory for enrolling in data science training courses in Port-au-Prince; many programs accept candidates with relevant undergraduate backgrounds.
Businesses in Port-au-Prince leverage data science for growth by improving decision-making, optimizing operations, and enhancing customer experiences.
In finance, data science is applied to risk management, fraud detection, and predictive analytics.
Data science contributes to e-commerce by powering recommendation systems, personalized marketing, and demand forecasting.
In cybersecurity, data science detects anomalies, identifies patterns, and enhances threat detection and prevention measures.
In manufacturing and supply chain management, data science optimizes production processes, predicts demand, and improves logistics efficiency.
The Datamites™ Certified Data Scientist course provides a comprehensive curriculum covering programming, statistics, machine learning, and business knowledge. Focused on Python as the primary language and accommodating those familiar with R, the course establishes a robust foundation in data science. Upon completion, participants receive an IABAC™ certificate, preparing them for success as skilled data science professionals.
While a background in statistics can be advantageous, it is not always a requirement for entering a data science career in Port-au-Prince. Proficiency in relevant tools, programming languages, and effective problem-solving skills are often prioritized.
For individuals in Port-au-Prince venturing into the data science field, several entry-level training options exist, such as the Certified Data Scientist, Data Science Foundation, and Diploma in Data Science courses.
Certainly, in Port-au-Prince, DataMites provides specialized courses for professionals aiming to augment their skills. These include Statistics for Data Science, Data Science with R Programming, Python for Data Science, Data Science Associate, and certifications in Operations, Marketing, HR, and Finance.
The data science course in Port-au-Prince offered by DataMites spans 8 months.
Career mentoring sessions at DataMites follow an interactive format, offering personalized guidance on resume building, interview preparation, and career strategies. These sessions provide valuable insights and tactics to enrich participants' professional journeys in data science.
Upon completing DataMites' Data Science Training in Port-au-Prince, participants receive the prestigious IABAC Certification. This globally recognized certification validates their proficiency in data science concepts and applications, enhancing their credibility in the field.
To excel in data science, it's crucial to establish a strong foundation in mathematics, statistics, and programming. Develop analytical skills, achieve proficiency in languages like Python or R, and gain hands-on experience with extensive datasets and essential tools like Hadoop or SQL databases.
Opting for online data science training in Port-au-Prince from DataMites provides flexibility, allowing learners to progress at their own pace. It overcomes geographical limitations, making courses accessible to anyone with an internet connection. The training ensures a comprehensive syllabus aligned with industry needs and features skilled instructors for an interactive learning experience.
The data science training fee in Port-au-Prince ranges from HTG 70,002 to HTG 175,026, depending on the specific program.
Certainly, DataMites' Data Scientist Course in Port-au-Prince includes hands-on learning with more than 10 capstone projects and a dedicated client/live project, providing practical experience relevant to the industry.
Instructors chosen 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, tailored to accommodate participants' preferences.
The FLEXI-PASS option in DataMites' Certified Data Scientist Course allows participants to join multiple batches, enabling them to revisit topics, clarify doubts, and enhance their understanding across various sessions for a comprehensive learning experience.
Certainly, DataMites issues a Certificate of Completion for the Data Science Course, validating participants' proficiency in data science and enhancing their credibility in the job market.
Certainly. A valid Photo ID Proof, such as a National ID card or Driving License, is required to obtain a Participation Certificate and schedule the certification exam as necessary.
In case of a missed session in the DataMites Certified Data Scientist Course in Port-au-Prince, participants usually have the option to access recorded sessions or participate in support sessions, ensuring they can catch up on missed content and stay on track with the course.
Certainly, potential participants at DataMites can attend a demo class before making any payment for the Certified Data Scientist Course in Port-au-Prince, allowing them to evaluate the teaching style, course content, and overall structure.
DataMites sets itself apart by integrating internships into its certified data scientist course in Port-au-Prince, providing a unique learning experience that combines theoretical knowledge with practical industry exposure, enhancing skills and increasing job opportunities in the evolving field of data science.
Upon successfully finishing the Data Science training, you will receive an internationally recognized IABAC® certification, validating your expertise in the field and enhancing your employability globally.
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.