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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 is the practice of extracting insights and knowledge from data, employing techniques such as statistics, machine learning, and data analysis. It encompasses the entire data lifecycle, from collection to visualization.
Critical skills for aspiring Data Scientists encompass proficiency in programming languages, data manipulation, statistical analysis, machine learning, and effective communication to articulate findings clearly.
While a bachelor's degree in a related field is common, many Data Scientists hold advanced degrees such as a master's or Ph.D. Essential qualifications include relevant skills, experience, and a strong foundation in mathematics and programming.
Data Science operates by collecting and analyzing extensive datasets to reveal patterns, trends, and insights. It involves utilizing statistical methods, machine learning algorithms, and programming languages like Python or R to extract valuable information.
The Certified Data Scientist Course is a standout option in Poland, covering crucial data science skills like programming, statistics, and machine learning. Participants gain hands-on experience, preparing them for successful careers in the dynamic field of data science.
Individuals with backgrounds in mathematics, statistics, computer science, or related fields are eligible for Data Science Certification Courses. These courses also benefit professionals looking to enhance their analytical skills or transition into the field.
Statistics is pivotal in data science, allowing analysts to derive meaningful insights from data. This encompasses utilizing descriptive statistics to summarize data and inferential statistics for making predictions and decisions based on sampled data.
Enrolling in Data Science Bootcamps can be advantageous for swiftly acquiring skills. These programs offer practical experience, mentorship, and networking opportunities, accelerating entry into the field. Success, however, hinges on individual commitment and the quality of the selected bootcamp.
Embark on the journey by establishing a robust foundation in mathematics and programming. Gain practical experience with real-world datasets, explore online courses, engage in projects, and construct a portfolio showcasing your skills. Networking with professionals in the field can also provide valuable insights.
Data Science in finance is employed for risk management, fraud detection, customer segmentation, and algorithmic trading. It utilizes predictive modeling and analytics to optimize decision-making processes, enhance customer experiences, and identify irregularities in financial transactions.
Frequent challenges in Data Science Projects include issues with data quality, model interpretability, and scalability. Tackling these challenges involves meticulous data preprocessing, utilizing explainable AI techniques, and optimizing algorithms for efficient processing.
In Poland, Data Scientists usually initiate their careers as analysts, progressing to more senior roles or specializing in areas such as machine learning engineering or data architecture. Career advancement is commonly achieved through ongoing learning, networking, and accumulating hands-on experience.
Participating in Data Science Internships is vital for gaining practical exposure to real-world projects, fostering hands-on skill development, and gaining insights into the industry. Internships not only bolster resumes but also facilitate networking, often leading to subsequent full-time employment opportunities.
According to Payscale, Data Scientists in Poland can expect a substantial annual salary, averaging at €117,779. This reflects the high demand for their expertise in leveraging data for strategic decision-making. The impressive compensation underscores their crucial role in driving innovation and efficiency in the dynamic landscape of Poland's industries.
Data Scientists are tasked with gathering, processing, and analyzing extensive datasets to extract actionable insights. They develop predictive models, design experiments, and convey findings to guide strategic decision-making. Collaborating with cross-functional teams, they contribute to problem-solving and foster innovation within the organization.
Data Science empowers retailers to scrutinize customer behavior, preferences, and purchase history, facilitating effective segmentation. Leveraging machine learning algorithms, businesses can customize shopping experiences, recommend products, and refine marketing strategies, ultimately elevating customer satisfaction and loyalty.
Data Science is widely applied across sectors including finance, healthcare, e-commerce, manufacturing, and telecommunications. Its versatile tools and methodologies contribute to enhanced decision-making, efficiency, and innovation in diverse fields.
The Data Science project lifecycle includes defining objectives, data collection, exploratory data analysis, model development, validation, deployment, and continuous monitoring. Each stage is essential to ensure alignment with business goals and the delivery of meaningful insights.
In manufacturing and supply chain management, Data Science optimizes processes by predicting equipment failures, improving demand forecasting, and enhancing inventory management. It enhances operational efficiency, cuts costs, and streamlines supply chain operations.
Data Science is pivotal in e-commerce, analyzing customer behavior, preferences, and transaction data. Recommendation systems, driven by machine learning algorithms, personalize user experiences, suggest products, and boost customer engagement, ultimately leading to increased sales and satisfaction.
Data Science functions by collecting and analyzing extensive datasets to reveal patterns, trends, and insights. It involves the application of statistical methods, machine learning algorithms, and programming languages like Python or R to extract valuable information.
DataMites offers a diverse array of data science certifications in Poland, including the renowned Certified Data Scientist course. They provide specialized programs like Data Science for Managers, Data Science Associate, and Diploma in Data Science, catering to various skill levels and professional requirements.
Yes, participants are required to present a valid photo identification proof, such as a national ID card or driver's license, to receive their participation certificate and, if needed, to schedule the certification exam during the data science training sessions.
For beginners in Poland, DataMites offers foundational data science training through courses like Certified Data Scientist, providing comprehensive skills. Courses like Data Science in Foundation and the Diploma in Data Science offer beginner-friendly tracks, ensuring a solid understanding of fundamental concepts for individuals entering the dynamic field of data science.
The duration of DataMites' data scientist courses in Poland varies from 1 to 8 months, depending on the course level and depth of content.
No prerequisites are necessary for enrolling in the Certified Data Scientist Training in Poland. The course is tailored for beginners and intermediate learners entering the field of data science.
Enrolling in DataMites' online data science training in Poland provides the flexibility to learn from any location, overcoming geographical constraints. The interactive online platform encourages engagement through discussions, forums, and collaborative activities, enriching the overall data science training experience.
DataMites' data science training in Poland features a structured fee range from PLN 43,995 to PLN 52,70, offering participants flexibility in choosing programs that suit their budget. The training covers a diverse curriculum, ensuring comprehensive skill development for individuals at different levels, contributing to the rising demand for proficient data scientists in the dynamic Polish market.
Indeed, DataMites offers specialized data science courses for Polandian professionals, covering Statistics, Python, and Certified Data Scientist Operations. Tailored options like Data Science with R Programming and Certified Data Scientist Courses in Marketing, HR, and Finance specifically address the needs of working professionals, ensuring targeted skill enhancement.
The DataMites Certified Data Scientist Course in Poland is a globally sought-after and comprehensive program in Data Science and Machine Learning. It is meticulously updated to meet industry needs, focusing on a job-oriented approach, equipping participants with essential skills for success in the dynamic field of data science.
Instructors at DataMites are carefully chosen based on their elite status, with faculty members having real-time experience from top companies and prestigious institutes like IIMs conducting the data science training sessions.
Certainly, upon successfully completing the data science course in Poland with DataMites, participants receive a prestigious certification, validating their proficiency in the field.
DataMites acknowledges that unforeseen circumstances may cause participants to miss training sessions in Poland. In such cases, recorded sessions are accessible for review, enabling participants to catch up on missed content. Additionally, one-on-one sessions with trainers are available to address queries and clarify concepts covered during the missed session, ensuring a comprehensive learning experience.
Indeed, DataMites provides Data Science Courses with internship opportunities in Poland, offering valuable hands-on experience with AI companies.
The Flexi-Pass at DataMites in Poland provides participants with flexible learning options, allowing them to customize their training schedule based on personal preferences. This accommodates busy schedules, ensuring individuals can pursue data science training at their convenience.
The ideal choice for managers or leaders aiming to incorporate data science into decision-making processes is the "Data Science for Managers" course offered by DataMites.
Certainly, in Poland, DataMites provides help sessions for participants, offering additional support and clarification on specific data science topics to ensure a comprehensive understanding.
DataMites' career mentoring sessions in Poland follow an interactive format, guiding participants on industry trends, resume building, and data science interview preparation to enhance their employability in the data science field.
DataMites provides data science course training in Poland through online data science course training in Poland and self-paced methods, ensuring flexibility and personalized learning experiences.
Yes, DataMites offers a trial class option in Poland, providing participants with a preview of the training content and learning environment before committing to the fee.
Certainly, DataMites ensures the inclusion of live projects in their Data Scientist Course in Poland, featuring over 10 capstone projects and hands-on client/live project experiences.
Upon successfully completing Data Science Training in Poland, DataMites awards participants with IABAC Certification, recognizing their proficiency in data science.
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.