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کارگاه آموزشی زبان برنامه نویسی پایتون در تاریخسه‌شنبه ۲۳ خردادبه پایان رسیده است. (جزئیات بیشتر)

کارگاه آموزشی زبان برنامه نویسی پایتون

شروع:
شنبه ۱۶ اردیبهشت ۹۶ ۱۷:۰۰
پایان:
سه‌شنبه ۲۳ خرداد ۹۶ ۲۱:۰۰
کارگاه آموزشی زبان برنامه نویسی پایتون
برگزارکننده‌ی رویداد
مهلت ثبت‌نام برای این رویداد به پایان رسیده است.

توضیحات بیشتر

 

عنوان دوره

زبان برنامه نویسی پایتون  در راستای آنالیز دیتا

Python in Data Science Applications

 

**** عصر روزهای شنبه و 3 شنبه ( 10 جلسه 4 ساعته) ساعت 17 الی 21



  • خلاصه :  

 پایتون زبان برنامه نویسی رو به رشدی  است که امروزه در علوم و کاربردهای مختلف شنیده می شود  و بسیار از سیستم های آنالیز کلان داده و تجزیه و تحلیل سیستم ها بر اساس استفاده از آن طرح ریزی و دنبال می گردند.

پایتون  به دلیل سادگی و کارایی فوق العاده در اولین انتخاب های برنامه نویسان و به خصوص پروژه های کلان قرار می گیرد. هسته مرکزی پایتون همراه با کتابخانه های مختلفی که روزانه به وفور به صورت اکثریت رایگان در اختیار کاربران قرار می گیرند قدرت فوق العاده به کاربران در صنایع مختلف می دهد .

این دوره به دوستانی که به تحلیل دیتا علاقه مند هستند توصیه می شود.

 

  • مدت دوره:  40 ساعت ( 10 جلسه 4 ساعته)

 

  • پيش نياز:  آشنایی اولیه با مفاهیم اولیه برنامه نویسی و علاقه مند به یادگیری مباحث روز فناوری در علوم رایانه

 

  • مخاطبین: علاقه مندان علوم رایانه – علوم ریاضیات کاربردی- ( ترجیحا دانشجویان و دانش آموختگان کارشناسی ارشد )

 

  • اهداف دوره: اشنایی با زبان مفسری پایتون با هدایت کاربر به سمت تحلیل  دیتا (  آنالیز عددی- متنی- وب – تصویری )

 

  • در انتهای اين دوره دانشجويان قادر خواهند بود:

دانشجویان با زبانی توانمند که امکان توسعه و کاربرد آن در علوم مختلف میسر است اشنا خواهند شد و همچنین در جلسات بخش دوم دوره با مباحث آنالیز دیتا و یادگیری ماشین – وب کاوی و... نیز به خوبی اشنا می شوند.

 

  • مدرس دوره:

مهدی حبیب زاده – دکتری علوم رایانه ( هوش مصنوعی) – دانشگاه کنکوردیا مونترال کانادا

 ***به مخاطبینی که در تمام جلسات این برنامه آموزشی حضور بهم رسانند از سوی مدرس و کافه آی تی گواهینامه حضور در دوره اعطا خواهد شد.

***شروع کلاس منوط به حد نصاب رسیدن ظرفیت کلاس می باشد.


عزیزان جهت هرگونه هماهنگی و سوال با شماره 88672920 تماس حاصل فرمایید.

  • سرفصل دوره:

 

Introduction to Python Programming (Level 01)

  • Introduction to Open-Source Language
    • Python Core and Versions
    • Pycharm, Anaconda
    • Jupyter, Qt console, Notebook, Ipython, Anaconda Navigator
    • Reserved Words and Naming Conventions

 

  • Python Data Structure
    • Arithmetic operations
    • Python Collections (Lists, Tuples, Sets and Dictionaries)
    • Import Clause
    • Copying Collections (Deep and Shallow Copy)
    • Intro to Classes, Functions
    • Read and write Output/Input
    • Formatting Output/Input and Dialog Boxes
    • Access and Permission
    • Handling I/O Exceptions
    • Typecasting and Parsing

 

  • Functions and Classes
    • Built-in Modules (Sys, Math, Time, Pickle, …)
    • Access Modifiers (Public- Private -Protected)
    • User-Defined Classes
    • Constructors, Copy Constructor, Object Instantiation
    • User-defined Methods
    • Set and Get methods
    • Finalizers
    • Overloading versus Overriding Methods
    • Four fundamental Object-oriented programming (OOP) concepts
    • Inheritance, Polymorphism, Abstraction and Encapsulation
    • Interfaces (Abstract base) and Packages

 

  • Regular Expressions
    • Built-in Modules (Re...)
    • Simple Character Matches
    • Special Characters
    • Greedy Matches
    • Grouping
    • Substituting
    • Splitting a given String
    • Compiling Regular Expressions

 

  • Serialization and Deserialization (Pickle…)

     

Python Programming Dives into Data Science (Level 02)

 

  • Data Integration
    • Plain Text (Standard and UTF-8)
    • Excel /CSV Format
    • Multimedia Files and Services (Read / Write)
    • Web Crawler (urllib, request, soup, scrapy…)
    • Data Serialization (Pickle, Dill, JSON, YAML…)
    • PyDI: Python Data Integration package
    • Introduction to Pentaho: Data Integration, Business Analytics and Big Data
    • Database Connectivity (SQL/NoSQL connections)

 

  • Essential Data Science Libraries
    • NumPy - Numeric Computation
    • Pandas - Data structures and Exploratory Analysis.
    • Matplotlib - Plotting and Visualization Tool
    • IPython - Interactive shell to Explore Data and Debug Errors.
    • SciPy - Extends NumPy with more Mathematical Functionality

 

  • Image Processing (Essential Framework)
    • Introduction to general concepts in image processing
    • Scipy - Basic Image Manipulation and Processing
    • PIL - Basics Creating an image. Save Image. Load Image. Show image
    • OpenCV - Designed to solve Computer Vision problem
    • Scikit-Image - Collection of Algorithms for Image Processing

 

  • Conventional Machine Learning (Essential Framework)
    • Scikit-learn Package (Installation and Implementation)
    • Learning models in sklearn
    • k-means Clustering, Decision Trees, Linear Regression,
    • K-Nearest-Neighbors, Predictive Models, Logistic Regression,
    • Support Vector Machines,
    • Dimensionality Reduction
    • K-Fold Cross-Validation and Confusion matrices

 

  • Deep Learning Package (Installation and Implementation)
    • GPU programming in Python (CUDA, …)
    • TensorFlow; High-performance serving system for machine learning models
    • TF Learn Introduction (A given Example)
    • TF-Slim Introduction (A given Example)
    • Caffe; Deep learning framework
    • Keras; Deep Learning library for Theano and TensorFlow

 

  • Web and Text Mining
    • Review on Web Crawler Library
    • Introduction to Natural language processing (NLP)
    • NLTK Exploration; The Natural Language Toolkit
    • NLTK Stanford; Sentiment Analysis and Text Classification
    • HAZM “Farsi Mining”; Library for Digesting Persian Text

 

  • Big data Framework
    • Introduction to big data frameworks
    • Hadoop Python MapReduce

 

منابع درسی:

 

Tutorial webpage:

 

 E- Book:

 Micha Gorelick and Ian Ozsvald , High Performance Python, O’Reilly Media, Inc. 2014

  • Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser , Data Structures and Algorithms in Python, John Wiley & Sons, Inc.2013
  • Robert Layton, Learning Data Mining with Python, Packt Publishing. 2015
  • Zachary Radtka and Donald Miner, Hadoop with Python, O’Reilly Media, Inc. 2016
  • Joe Minichino, Joseph Howse, Learning OpenCV3 Computer Vision with Python Second Edition, Packt Publishing, 2015
  • Jason Brownlee, Deep Learning with Python Develop Deep Learning Models On Theano and TensorFlow Using Keras, Machine Learning Mastery, 2016
  • Paweł Cichosz, Data Mining Algorithms: Explained Using R, John Wiley & Sons, Ltd, 2015
  • John Paul Mueller and Luca Massaron, Machine Learning for Dummies, John Wiley & Sons, 2016

 

telegram.me/itcafe

"یک فنجان قهوه با طعم نوآوری در کافه آی تی"

سخنرانان

دکتر مهدی حبیب زاده مطلق

دکتر مهدی حبیب زاده مطلق

سخنران، مدرس، مجری و مشاور علوم رایانه در دانشگاه و سازمان های حرفه ای ایران

OBJECTIVE
Software Developing, Machine Learning, Big Data Solutions, Image Processing, Computer Vision,
Database Management, Signal Processing, Statistical Analysis and Teaching.

PROFILE

• PhD, Computer Science, Concordia University, Montréal, Québec, Canada.
• Professional College certificate (AEC), Programming & Database, Vanier College, Montréal, Québec, Canada.
• 5+ years’ experience in working on Computer Programming and Databases.
• 5+ years’ experience in Big Data Analysis, Medical Image Processing, Medical Imaging, Machine learning, Data Mining, Pattern recognition, Data Structures and Performance Optimization.

• 5+ years’ experience in teaching, “both as an instructor and as a student mentor”.
• 1+ years’ experience in working on Big Data analysis and Statistical parametric vs. non-parametric methodologies.
• Programming background in Python, Java, C++, and MATLAB in Windows / Linux.
• Experience in SQL\ NoSQL Data Management (Oracle, Cassandra, MangoDB)
• Hands-on experience in statistical analysis, visualization and data mining (R, MATLAB).
• Communication skills in English (Full professional proficiency), French (Professional working proficiency) and Farsi.
• Member of Non-resident Iranian Elites Foundation.
• Image and Data Processing Scientist, Research and Clinical Center, Royan Institute, Iran.
• Data Scientist and Vocational Training Instructor, BI Dept., Mellat Bank, Iran.
• Dual nationality and citizenship (Canadian- Iranian).

EDUCATION AND TRAINING
PhD of Engineering, Computer Science (Machine Learning) Sept 2009 - Aug2015
Concordia University, Montréal, Québec, Canada.
AEC, Programming & Database (Java, Oracle, Linux) Sept 2015 - Dec 2015
Vanier Collège, Montréal, Québec, Canada.
Certificate, French Language Proficiency (Advanced) Oct 2009 - Feb 2010
Collège de Bois-de-Boulogne, Montréal, Québec, Canada.
Master of Science, Electrical & Computer Engineering Sept 2005- Apr 2008
Iran University of Science and Technology (IUST), Tehran, Iran.
Bachelor of Science, Electrical & Computer Engineering Sept 1998 – Jun 2003
Shahed University, Tehran, Iran.


ACADEMIC PUBLICATIONS

Working Paper:

M. Habibzadeh, N. Sodeifi, H. Baharvand. Evaluation and Treatment of Infertility Using Machine Learning and Image Processing Approaches. In preparation to: A biomedical Elsevier Journal (In progress).

M. Habibzadeh, A. Krzyżak, and T. Fevens. Feature Selection using RS-HDMR and Branch & Bound Algorithms for White Blood Cell Classification in Low Resolution Images. In preparation to: A biomedical Elsevier Journal (In progress).

Publications to Date:

M. Habibzadeh, A. Krzyżak, and T. Fevens. Comparative Study of Feature Selection for White Blood Cell Differential Counts in Low Resolution Images. ANNPR, Conference of Artificial Neural Networks in Pattern Recognition, volume 8774 of Lecture Notes in Artificial Neural Networks in Pattern Recognition, pages 216 227.Springer, 2014.

M. Habibzadeh, A. Krzyżak, and T. Fevens. White blood cell differential counts using convolutional neural networks for low resolution images. ICAISC, 12th International Conference on Artificial Intelligence and Soft Computing, volume 7895 of Lecture Notes in Computer Science, pages 263 274. Springer, 2013.

M. Habibzadeh, A. Krzyżak, and T. Fevens. Comparative Study of Shape, Intensity and Texture features and Support Vector Machine for White Blood Cell Classification. Journal of Theoretical and Applied Computer Science.7(1):20 35, 2013.

M. Habibzadeh, A. Krzyżak, and T. Fevens. Analysis of white blood cell differential counts using dual-tree complex wavelet transform and support vector machine classifier. International Conference on Computer Vision and Graphics, volume 7594 of Lecture Notes in Computer Science, pages 414 422. Springer, 2012.

A. Krzyżak, T. Fevens, M. Habibzadeh, and L. Jelen. Application of pattern recognition techniques for the analysis of histopathological images. Computer Recognition Systems 4, volume 95 of Advances in Intelligent and Soft Computing, pages 623 644. Springer, 2011.

M. Habibzadeh, A. Krzyżak, and T. Fevens. Application of pattern recognition techniques for the analysis of thin blood smear images. Journal of Medical Informatics & Technologies., 18(1):29 40, 2011.

M. Habibzadeh, A. Krzyżak, T. Fevens, and A. Sadr. Counting of RBCs and WBCs in noisy normal blood smear microscopic images. SPIE Medical Imaging, volume 7963, page 79633I, Feb. 2011.






ACADEMIC & PROFESSIONAL EXPERIENCE


Visiting Lecturer, Instructor, Invited Talk, and Data Scientist (R&D) at Applied Science, Electrical & Computer Depts., Various Science and Engineering Schools, Universities, E-Commerce centers, and Research Institutes - Iran. (Feb 2016 –Date).

• Collaboration with Sharif University, Tehran University, AUT university, Training Center of the National Iranian Oil Company, Ferdowsi University of Mashhad, Shahid Rajaee Teacher Training University, Alzahra University, Shahrood University of Technology, Islamic Azad University, Industrial Management Institute, Royan Stem Cells and Biomedical Research Institute, Mellat Bank, Eyvanakey University, Ghiaseddin Kashani Educational Institute, Sematec vocational training center.

• Teaching various applied mathematics, and informatics courses (e.g. Big Data Analysis, Applied Machine Learning, Image Processing, Pattern Recognition, Script Python Language Programming, Business Intelligence, Intro. to Web Applications, SQL and NoSQL Database Management).

• Co-supervising and monitoring graduate (M. Sc) students’ projects.

• Organize and teaching extracurricular activities such as vocational training activities, intensive workshops (e.g. Oracle Database System, Hadoop and Apache Spark, Python programming, Advanced Java programming, NoSQL, LaTex text Editor, R computing software) and journal clubs.

• Academic talks: Bigdata and Frameworks; New perspective to applied machine learning, Advanced topics in Machine learning (e.g. Deep learning and its implementation), Image processing and challenges in low quality samples, Automated extraction and parameterization of Big Data (e.g. HDMR approach and its implementation).


Software and Database Developer at Educational and Business projects, (Contract Job).

• Design and implementing software systems.
• Experienced on programming & software engineering skills using various programming languages including Python, Java, SQL, CQL, JASON, and HTML.

• Experience in Database including MongoDB, Cassandra, and Oracle.
• Experience with Visual Studio Environments, NetBeans, SQL Plus, Sublime Text 3, Pycharm, Mongo Booster, DataStax DevCenter, ...

Research, Teacher Assistant, Computer Vision Software Designer at Computer Science & Software Engineering Dept. Concordia University -Montréal, Québec, (Sept.2009 –Aug. 2015).

• Research on theoretical and implementation aspects concerning Medical Imaging, Computer-Aided Diagnosis, Image Processing, Machine Learning & Pattern Recognition including supervised, semi-supervised, and unsupervised learning methodologies, Probabilistic Models, Global Sensitivity Analysis and Deep Learning Algorithms.
• PhD Thesis: Computerized Classification of Particles in Thin Blood Smear Slides using Image Processing and Machine Learning Techniques.
• Knowledge in Complete Blood Count (CBC) and hematology science. Experience with very limited, low quality and missing data.
• Experience with large scale features (Extraction and Selection).
• Experience with Deep learning (e.g. Convolutional Neural Networks) Experience in statistical computing software (R, Matlab).
• Programming in C++ and Python in windows/ Linux.
• Experience in OpenCV, scikit-learn, pylearn2, Keras, Caffe machine
learning, matplotlib, NumPy & SciPy mathematical python libraries and Weka as a collection of machine learning algorithms.
• Experience in big data platforms (MapReduce, Hadoop and Spark).

• Instruct, tutor, assist and monitor students in different mathematical and computer science courses (e.g. Probability & Statistics for Comp. Sc, Math for Computer Science, Pattern
Recognition, Machine Learning, Intro. to Web Applications), and intensive training workshops (i.e, LaTeX instructor).
• Reviewer of articles for scientific journals (IEEE Transactions on Neural Networks and Learning Systems, BMC Medical Imaging, AI and Data Mining).
• Seven Publications in Microscopy Image Processing (up to Sept. 2015)


Lecturer and Teacher at Electrical & Computer Engineering Dept. Applied Science and Technology University -Tehran, Iran. (Sept.2007 –June. 2009).

• Teaching various mathematics, informatics, and telecommunication courses
• Supervising and monitoring undergraduate student projects.
• Keep updated with developments in subject area, teaching resources and methods.
• Participate and organize extracurricular activities such as vocational training activities, intensive workshops, social student activities, and journal clubs.

Telecommunication Research & Development team at Communications Regulatory Authority (CRA) - Tehran, Iran, (May. 2006 - Jul. 2009).

• Conduct data collection using various methods with strong attention to statistical details.
• Research on cutting-edge techniques and equipment.
• Prepare and analysis demographic and statistical data and information
• Prepare and/or proofread telecommunication proposal packets.
• Determine the needs of different user’s level of technical documentation.
• Monitor of project or contract regulations concerning programmatically and financially.
• Experience working with SPSS, MS Project, Linux, SQL server and R tools.

TECHNICAL COMPUTER SKILLS


Operating Systems: Linux, Microsoft Windows.
Application Software: Office Package, LaTeX, and Photoshop.
Programming Languages: C++, Python, Java, HTML 5.
Database Package: Oracle, Cassandra, MangoDB.
Bigdata Framework: Hadoop, Apache Spark.
Engineering Software: MATLAB, R, WEKA, and Orange.
Version control: GitHub.

برگزارکنندگان

کافه آی تی

کافه آی تی

مرکزنوآوری و فناوری فناپ

خدمات کافه آی تی به استارت آپ ها و ایده پردازان:
کارگاه های آموزشی
منتورینگ
فضای کاری
برگزاری رویداد (startuptime)
تیم سازی و شبکه سازی

آدرس:تهران خیابان آفریفا ( جردن شمالی)،‌ بعد از پل میرداماد،‌ بن بست قبادیان شرقی،‌ پلاک 3،‌ کافه آی تی