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 and knowledge from data through scientific methods, algorithms, and systems. It combines statistical analysis, programming, and domain expertise to make data-driven decisions and discover patterns within complex datasets.
Commonly used programming languages in data science include Python and R. Python's versatility and extensive libraries make it a preferred choice, while R is valuable for statistical analysis and visualization.
The mechanism of Data Science involves a cyclical process, including data collection, cleaning, exploration, modeling, validation, and interpretation. This iterative approach enables uncovering insights and informing decision-making.
Data Science is applied in various practical areas such as finance for risk analysis, healthcare for predictive modeling, marketing for customer segmentation, and technology for algorithm development. It enhances efficiency and decision-making across industries.
While a degree in data science, computer science, or related fields is beneficial, practical skills and experience are crucial. Many successful data scientists hold degrees in mathematics, statistics, engineering, or have interdisciplinary backgrounds.
Primary tools for data scientists include programming languages (Python, R), statistical software (SAS, SPSS), and frameworks (TensorFlow, scikit-learn). Visualization tools like Tableau and programming environments like Jupyter are also commonly used.
Beginner-friendly data science projects include predicting housing prices, sentiment analysis on social media, or developing a basic recommendation system. These projects offer hands-on experience in data manipulation, visualization, and foundational machine learning concepts.
Fundamental skills for aspiring data scientists include proficiency in programming languages, statistical analysis, machine learning, data wrangling, and effective communication. Critical thinking, problem-solving, and domain-specific knowledge are essential for success in the field.
In Rabat, a Data Scientist may progress from entry-level roles to Senior Data Scientist or Analytics Manager. Career paths can further lead to specialized roles, such as machine learning engineer or data science team lead, depending on expertise and experience.
Data Science is practically applied in Rabat across various industries, including finance for risk analysis, healthcare for predictive modeling, marketing for customer segmentation, and technology for algorithm development. It optimizes processes and informs decision-making.
Rabat recognizes the Certified Data Scientist Course as a premier option. With a curriculum spanning programming, machine learning, and data analysis, it prepares individuals for impactful roles in the field. Completion of this course is a valuable asset for aspiring data scientists in Rabat.
Yes, data science internships in Rabat carry significant value. They provide practical experience, exposure to real-world projects, and networking opportunities, enhancing employability in the competitive job market.
In Morocco, data scientists receive competitive compensation, boasting an average salary of MAD 150,000, as per Payscale. This underscores the lucrative nature of the data science industry in Morocco, a trend driven by the rising demand for experts proficient in data handling and interpretation.
Yes, freshers in Rabat can undergo data science training and secure jobs. Building a strong skill set, gaining practical experience through projects, and networking can increase opportunities in Rabat's growing data science job market. Continuous learning and staying updated on industry trends are key.
Individuals with an interest in data analysis, professionals seeking to enhance analytical skills, or those transitioning into data-centric roles are eligible for Data Science Certification Courses. A background in mathematics, statistics, computer science, or related fields is beneficial but not mandatory.
In e-commerce, data science analyzes user behavior and historical data to power recommendation systems. These systems enhance customer experience by providing personalized product suggestions, boosting engagement, and ultimately driving sales.
Data science optimizes manufacturing and supply chain processes by predicting demand, improving logistics, and enhancing quality control. It facilitates predictive maintenance, inventory management, and real-time analytics, leading to increased efficiency.
Industries actively recruiting Data Scientists include finance for risk analysis, healthcare for predictive modeling, technology for algorithm development, and e-commerce for customer analytics. Emerging sectors like smart cities and renewable energy also demonstrate a growing demand.
Yes, transitioning from a non-coding background to data science is possible. Learning programming languages, gaining statistical and machine learning skills, and building a strong foundation through online courses and projects can facilitate a successful career transition.
To kickstart a data science career in Rabat, one should acquire relevant skills through online courses, build a portfolio of projects, and engage with local data science communities. Networking with professionals, considering internships, and staying updated on industry trends are crucial steps for success in Rabat's data science job market.
Acknowledged globally, the DataMites Certified Data Scientist Course in Rabat is a premier, job-focused program in Data Science and Machine Learning. Regular updates in line with industry standards ensure a structured learning process, facilitating effective and streamlined skill acquisition.
The Certified Data Scientist Training in Rabat has no prerequisites, making it suitable for beginners and intermediate learners in the field of data science.
DataMites in Rabat presents a comprehensive suite of data science certifications, featuring the Certified Data Scientist, Data Science for Managers, Data Science Associate, Diploma in Data Science, Statistics for Data Science, Python for Data Science, and specialized courses in Marketing, Operations, Finance, HR, and R. This varied offering ensures a tailored approach to different skill levels and industry demands.
Beginners in Rabat can embark on their data science journey with DataMites, offering accessible training like Certified Data Scientist, Data Science in Foundation, and Diploma in Data Science. These beginner-level courses lay a strong foundation, providing essential skills for those new to the field.
DataMites in Rabat provides specialized data science courses designed for working professionals. These include Statistics for Data Science, Data Science with R Programming, Python for Data Science, Data Science Associate, and Certified Data Scientist courses in Operations, Marketing, HR, and Finance. These courses are crafted to cater to the specific requirements of professionals seeking to expand their knowledge in targeted areas of data science.
The duration of DataMites data scientist courses in Rabat varies, spanning from 1 to 8 months. This flexibility accommodates diverse learning preferences and the depth of the chosen course.
Participating in online data science training in Rabat with DataMites provides the flexibility to learn from any location, breaking geographical barriers. The interactive online platform fosters engagement through discussions, forums, and collaborative activities, contributing to an enriched data science training experience.
At DataMites, data science course training is available through online data science training in Rabat and self-paced methods, offering flexibility for participants to tailor their learning journey.
DataMites' data science training in Rabat offer a comprehensive fee structure, with prices ranging from MAD 5239 to MAD 13099, ensuring accessibility for a diverse range of participants.
Participants attending data science training sessions must bring a valid photo identification proof, such as a national ID card or driver's license. This is essential for obtaining a participation certificate and scheduling any required certification exams.
Participants missing a data science session in Rabat can catch up through session recordings. This convenient option allows you to stay updated with the material at your own pace, even if you couldn't be part of the live session. Exclusive Q&A sessions are also arranged for those who miss the live training.
Attend our free demo class for data science training in Rabat. It's an opportunity to assess the content and teaching style, providing you with a clear understanding of our approach before you commit to the training fee.
Indeed, DataMites integrates internship experiences with AI companies into their Data Science Courses in Rabat, providing real-world exposure.
Absolutely, there is an option for participants in Rabat to attend help sessions aimed at improving their understanding of specific data science topics. These sessions are designed for interactive discussions, addressing queries, and reinforcing key concepts. This option underscores the commitment to providing comprehensive support, ensuring that participants in Rabat can navigate data science topics effectively.
Indeed, the Data Scientist Course at DataMites in Rabat includes live projects, featuring 10+ capstone projects and a client/live project for hands-on, practical learning experiences.
DataMites grants IABAC certifications following Data Science Training in Rabat, acknowledging participants' mastery and providing industry-standard validation.
The Flexi-Pass in data science training introduces a revolutionary approach, empowering learners to shape their educational path. This model enables students to customize their curriculum, select specific modules, and dictate their learning pace. Accommodating various schedules and preferences, Flexi-Pass facilitates a personalized and effective mastery of data science concepts.
The career mentoring sessions within the training adhere to a clear structure. Participants have the opportunity for one-on-one interactions with experienced mentors. These sessions cover a spectrum of topics, including setting career objectives, refining specific skills, and navigating the intricacies of the data science job landscape. The structured approach guarantees that participants receive customized advice and support, empowering them to navigate their career paths effectively.
Managers and leaders seeking to integrate data science into decision-making processes will find DataMites' "Data Science for Managers" course most suitable, offering strategic insights and applications.
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.