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 insights from vast datasets using statistical methods, machine learning, and domain expertise. It encompasses data cleaning, exploration, modeling, and interpretation, driving informed decision-making and business strategy.
Critical skills include proficiency in programming languages (Python, R), statistical analysis, machine learning algorithms, data visualization, and effective communication. Problem-solving, curiosity, and domain-specific knowledge are also crucial for success.
Begin by mastering foundational concepts in mathematics, statistics, and programming. Explore online courses and local workshops, engage with the Data Science community through meetups, and consider pursuing relevant academic degrees or certifications.
While coding skills enhance capabilities, individuals without coding experience can enter Data Science using tools with graphical interfaces. However, learning languages like Python is advisable for a comprehensive skill set and better career prospects.
Data Science functions through a cyclical process involving problem definition, data collection, cleaning, exploratory data analysis, model building, evaluation, and deployment. Collaboration between data professionals and domain experts is crucial for effective results.
A strong foundation in mathematics, statistics, or computer science is typically required. Many Data Scientists have bachelor's, master's, or PhD degrees in related fields. Advanced degrees provide depth, but practical skills and experience are equally important.
Proficiency in Python is highly recommended for its versatility, extensive libraries, and community support. While other languages like R are used, Python's industry prevalence makes it a virtual prerequisite, facilitating collaboration and adaptability in the dynamic field of Data Science.
In Ankara, Data Scientists typically begin as Analysts, advancing to roles like Senior Data Scientist or Machine Learning Engineer. With experience, they may take on managerial or specialized roles, contributing to decision-making processes and the implementation of advanced analytics solutions.
Data Science Certification Courses are open to various individuals, including recent graduates, working professionals, or those seeking a career change. Prerequisites often include basic quantitative skills, a strong analytical mindset, and a desire to learn.
Data Scientists in Ankara, Turkey, experience attractive compensation, enjoying an estimated annual salary of 160,000 TRY, as reported by Salary Explorer. This reflects the city's recognition of the value and expertise Data Scientists bring to the table, making Ankara an appealing destination for professionals seeking rewarding careers in the field.
Build a portfolio showcasing diverse projects. Highlight skills in data cleaning, exploratory data analysis, machine learning, and effective data visualization. Clearly articulate the business impact of each project, sharing code on platforms like GitHub to demonstrate proficiency.
Demand for Data Scientists is currently high in sectors such as finance, healthcare, e-commerce, and technology. Major cities like Ankara and Istanbul are hubs, with companies leveraging data for strategic decision-making and innovation.
Current trends include explainable AI, automated machine learning (AutoML), and advancements in natural language processing (NLP). Ethical considerations, responsible AI practices, and the integration of data science into business strategies are also prominent.
While not always mandatory, having a postgraduate degree can enhance eligibility for Data Science training courses in Ankara. Many programs accept individuals with strong quantitative skills, relevant work experience, or a bachelor's degree in a related field.
Big Data and Data Science intersect as Data Science utilizes techniques to analyze and derive insights from large datasets, which is characteristic of Big Data. The two fields share tools and methodologies to extract valuable information from massive and complex data sets.
Data Science finds applications in finance, healthcare, e-commerce, and more. It's used for fraud detection in finance, improving diagnostics in healthcare, customer segmentation in marketing, and optimizing operations in various industries.
Data Science is a broader field encompassing data analysis, statistical modeling, and machine learning. Machine Learning is a subset, focusing specifically on algorithms that enable computers to learn from data and make predictions or decisions without explicit programming.
Construct a portfolio with diverse projects showcasing skills in data cleaning, exploratory data analysis, machine learning, and effective data visualization. Clearly document your approach, highlight business impacts, and share code on platforms like GitHub to demonstrate practical proficiency.
Data Science contributes to Ankara enterprises by optimizing processes, enhancing decision-making through predictive analytics, and fostering innovation. It aids in efficient resource allocation, customer satisfaction improvement, and overall competitiveness in the evolving business landscape.
Elevate your data science expertise with the Certified Data Scientist Course in Ankara. This program offers a well-rounded curriculum covering essential aspects such as data analysis, machine learning, and statistical modeling, empowering participants with practical skills and a recognized certification for impactful roles in the industry.
Distinguished as the world's most popular and comprehensive, the DataMites Certified Data Scientist Course is meticulously updated to align with industry requirements. This job-oriented program boasts a structured learning approach, facilitating lean learning for participants to master Data Science and Machine Learning effectively.
The fee structure for DataMites' data science training programs in Ankara ranges from TRY 15,679 to TRY 39,203, providing participants with flexible options to choose the program that aligns with their learning goals and budget.
Ankara offers accessible training for beginners in data science with programs like the Certified Data Scientist, Data Science in Foundation, and Diploma in Data Science. These courses provide a solid foundation, equipping individuals with essential skills to kickstart their data science careers effectively.
Ankara caters to the professional development of its workforce with specialized data science courses by DataMites. Tailored for working professionals, offerings include Statistics for Data Science, Data Science with R Programming, Python for Data Science, and sector-specific certifications in operations, marketing, HR, and finance, providing advanced knowledge for career augmentation.
DataMites' data science courses in Ankara offer flexibility, with durations spanning from 1 to 8 months. This adaptability caters to individuals' preferences and allows them to choose courses based on their desired level of depth and commitment.
With DataMites in Ankara, online data science training offers the flexibility of learning from any location. Participants can access quality education without being bound by geographical constraints. The interactive platform encourages engagement through discussions, forums, and collaborative activities, ensuring a comprehensive data science training experience.
Instructors at DataMites are chosen based on elite criteria, comprising industry experts and faculty members with real-world experience from esteemed institutions like IIMs. This ensures a blend of practical insights and academic rigor in data science training sessions.
It is mandatory for participants to bring photo identification proof, such as a national ID card or driver's license, for the issuance of participation certificates and scheduling certification exams, if applicable, during the data science training sessions.
DataMites offers a comprehensive suite of data science certifications in Ankara. From the coveted Certified Data Scientist program to specialized courses like Data Science for Managers and Data Science Associate, participants can choose a path aligned with their career goals. Tailored modules such as Statistics for Data Science, Python for Data Science, and sector-specific tracks like Data Science in Finance and HR enhance the depth of expertise.
Participants who miss a data science training session in Ankara have the option to request a makeup session, ensuring they don't miss crucial content. Recorded sessions and comprehensive materials are also provided to support independent learning and catch up on missed material.
Absolutely, before committing to the data science training fee in Ankara, interested individuals can participate in a free demo class provided by DataMites. This gives them firsthand experience of the training structure and content, helping them make an informed decision.
Specifically designed for managers, the "Data Science for Managers" course equips leaders with the knowledge and skills needed to seamlessly integrate data science into their decision-making processes.
In Ankara, participants enrolled in DataMites' Data Science Training have the option to attend help sessions for a better understanding of specific topics. These sessions provide additional assistance, fostering a supportive learning environment and enhancing comprehension.
DataMites in Ankara includes live projects, comprising 10+ capstone projects and 1 client project, in its Data Scientist course, ensuring participants gain practical experience in real-world scenarios.
DataMites' Flexi-Pass concept in data science training offers participants the flexibility to select their preferred training schedule. This adaptive approach accommodates varying time constraints, enabling individuals to seamlessly integrate learning into their existing commitments.
The career mentoring sessions at DataMites are structured to guide participants through goal setting, skill enhancement, and understanding the current job market trends. This personalized approach ensures that individuals receive tailored advice to excel in their data science careers.
Participants at DataMites in Ankara can choose from various training methods for data science courses, with options like online data science training in Ankara and self-paced training, ensuring adaptable and personalized learning experiences.
The Certified Data Scientist Training in Ankara has no prerequisites, welcoming beginners and intermediate learners in the field of data science. This inclusive approach ensures accessibility for individuals with varied backgrounds and levels of expertise.
DataMites' Data Science Training in Ankara culminates in an IABAC Certification, providing participants with industry-recognized validation for their skills and knowledge.
DataMites in Ankara integrates internships with AI companies into its data science courses, offering participants practical exposure and industry experience.
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.