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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 complex data using statistical analysis, machine learning, and data visualization. It spans the entire data lifecycle, from collection to interpretation, to inform decision-making and solve complex problems across various domains.
Aspiring Data Scientists need proficiency in programming languages, data manipulation, statistical analysis, and machine learning. Strong communication, problem-solving, and critical thinking skills, along with a continuous learning mindset, are crucial for success in this dynamic field.
Certification courses in Data Science are open to individuals with backgrounds in mathematics, statistics, computer science, or related fields. Professionals seeking to enhance their analytical skills or transition into the field also find these courses beneficial.
While a bachelor's degree in a related field is common, advanced degrees like a master's or Ph.D. are advantageous for a career in Data Science. Relevant skills, practical experience, and a strong foundation in mathematics and programming are key contributors to success.
Data Science involves extracting insights and building predictive models from complex data using techniques like machine learning. On the other hand, Business Analytics utilizes statistical analysis and descriptive analytics to inform business decisions, focusing on optimizing decision-making. While there is overlap, Data Science tends to be more exploratory and predictive, while Business Analytics is often prescriptive.
The Certified Data Scientist Course takes precedence in Addis Ababa's data science landscape. This certification program covers essential skills, including programming and machine learning, providing participants with a solid foundation and practical experience for a prosperous data science journey.
Statistics is foundational in Data Science, providing tools for data analysis, hypothesis testing, and model validation. It ensures robust and meaningful interpretations of data, guiding decision-making processes.
In Addis Ababa, a Data Scientist typically begins as an analyst, advancing to senior roles or specializing as a machine learning engineer. Continuous learning, networking, and gaining hands-on experience contribute to career growth.
In finance, Data Science is applied for risk management, fraud detection, customer segmentation, and algorithmic trading. It enhances decision-making processes, improves customer experiences, and fosters innovation within the sector.
Common challenges include data quality issues, model interpretability, and scalability. Rigorous data preprocessing, using explainable AI techniques, and optimizing algorithms address these challenges and ensure project success.
Data Science Internships offer practical experience with real-world projects, bridging the gap between academic learning and industry demands. They enhance skills, provide exposure to industry practices, and often lead to valuable employment opportunities.
Begin by acquiring relevant educational qualifications, developing programming and statistical skills, engaging in hands-on projects, and networking within the local data science community. Consider pursuing specialized certifications to enhance your profile.
Data Scientists collect, process, and analyze data to derive valuable insights. They develop predictive models, create data visualizations, and communicate findings to inform strategic business decisions. Collaboration with cross-functional teams is crucial for achieving organizational goals.
In e-commerce, Data Science analyzes customer behavior and transaction data to provide personalized recommendations. Recommendation systems, driven by machine learning algorithms, enhance user experiences, drive engagement, and contribute to increased sales and customer satisfaction.
The operational process involves defining problems, collecting and preprocessing data, exploratory data analysis, model development, validation, deployment, and continuous monitoring. Collaboration and effective communication are integral components throughout the process.
Data Science finds extensive applications in industries such as finance, healthcare, e-commerce, manufacturing, telecommunications, and energy. Its versatile tools contribute to improved decision-making, efficiency, and innovation across diverse sectors.
The Data Science project lifecycle includes defining objectives, data collection and preprocessing, exploratory data analysis, model development, validation, deployment, and continuous monitoring. Each stage is crucial for ensuring alignment with business objectives and providing meaningful insights.
In manufacturing and supply chain management, Data Science optimizes processes by predicting equipment failures and streamlines operations by improving demand forecasting and enhancing inventory management. It contributes to increased efficiency, reduced costs, and improved overall operational performance.
In Addis Ababa, Data Scientists receive competitive salaries, akin to global standards. According to Indeed, the average salary for a Data Scientist in the United States is $123,442 per year. This suggests that data scientists in Addis Ababa also enjoy substantial compensation, emphasizing the high value placed on their expertise in this rapidly evolving field.
Engaging in Data Science Bootcamps can be valuable for swiftly acquiring skills. These programs provide practical experience, mentorship, and networking chances, expediting one's entry into the field. Nonetheless, the degree of success hinges on individual dedication and the caliber of the bootcamp itself.
Yes, DataMites is attuned to the requirements of working professionals, presenting specialized data science courses like Statistics, Python, and Certified Data Scientist Operations. Tailored courses in Data Science with R Programming, and Certified Data Scientist courses for Marketing, HR, and Finance provide targeted insights and skill development opportunities.
Positioned as the world's most popular and comprehensive Data Science and Machine Learning course, the DataMites Certified Data Scientist Course in Addis Ababa is known for its job-oriented focus. Rigorously updated to meet industry requirements, the course is finely tuned to provide a structured learning path, making it a preferred choice for individuals pursuing a successful career in data science.
There are no prerequisites for undertaking Certified Data Scientist Training in Addis Ababa, designed for beginners and intermediate learners in the field of data science.
DataMites excels in delivering data science certifications in Addis Ababa, offering a spectrum of courses to meet diverse educational needs. The Certified Data Scientist course takes precedence, providing an extensive skill set. Tailored certifications like Data Science for Managers and Data Science Associate accommodate various proficiency levels.
The Diploma in Data Science ensures a comprehensive education. Supplementary courses in Statistics, Python, and domain-specific applications in Marketing, Operations, Finance, HR contribute to a well-rounded learning experience, positioning DataMites as a top choice for quality data science education in Addis Ababa.
Beginner-level data science training in Addis Ababa is readily available through DataMites. The Certified Data Scientist course imparts foundational skills, and Data Science in Foundation introduces fundamental concepts. The Diploma in Data Science offers a comprehensive curriculum tailored for beginners, ensuring a holistic understanding. These courses collectively serve as an accessible starting point for individuals entering the dynamic and evolving field of data science in Addis Ababa.
The duration of DataMites' data scientist courses in Addis Ababa is flexible, lasting from 1 to 8 months, contingent on the course level.
Yes, participants are required to present a valid photo identification proof, like 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.
DataMites' data science training in Addis Ababa features a fee structure spanning from ETB 29,901 to ETB 74,763, providing participants with diverse and affordable choices to accommodate their specific learning requirements and budget constraints.
Trainers at DataMites are selected based on their elite status, featuring faculty members with real-time experience from leading companies and prestigious institutes like IIMs who conduct the data science training sessions.
If a participant misses a data science training session in Addis Ababa, DataMites provides recorded sessions, allowing individuals to revisit the content. To further support their understanding, participants can schedule one-on-one sessions with trainers, ensuring that any questions or uncertainties related to the missed session are addressed for a seamless learning experience.
Certainly, participants in Addis Ababa can access help sessions with DataMites, ensuring additional assistance and clarity on specific data science topics during their training.
Certainly, before committing to the data science training fee in Addis Ababa with DataMites, participants can attend a demo class to assess the course and ensure it aligns with their learning expectations.
Yes, DataMites includes internships with AI companies in their Data Science Courses in Addis Ababa, ensuring practical exposure for participants.
Tailored for managers and leaders, "Data Science for Managers" at DataMites is the ideal choice for integrating data science into decision-making processes.
DataMites' online data science training in Addis Ababa offers the advantage of flexible learning from any location, breaking down geographical barriers. The interactive online platform facilitates engagement through discussions, forums, and collaborative activities, enhancing the data science training experience.
Yes, DataMites offers live projects as an integral part of their Data Scientist Course in Addis Ababa, presenting 10+ capstone projects and a valuable client/live project for hands-on experience.
Indeed, participants successfully finishing the data science training course in Addis Ababa with DataMites receive a certification, highlighting their mastery and achievement in the domain.
In Addis Ababa, the Flexi-Pass concept at DataMites allows participants to mold their data science training schedule, ensuring flexibility and convenience in pursuing their learning objectives.
DataMites offers data science course training in Addis Ababa through online data science training in Addis Ababa and self-paced methods, ensuring participants benefit from flexibility and personalized learning experiences.
DataMites issues IABAC Certification to participants upon finishing Data Science Training in Addis Ababa, recognizing their proficiency and knowledge in data science.
DataMites' career mentoring sessions in Addis Ababa are formatted to provide participants with tailored guidance on resume enhancement, interview preparation, and industry insights, ensuring a holistic approach to their data science career development.
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.