Instructor Led Live Online
Self Learning + Live Mentoring
Customize Your Training
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 data through statistical analysis, machine learning, and data visualization. It encompasses the entire data lifecycle, from collection to interpretation, and contributes to informed decision-making.
Common challenges include data quality issues, model interpretability, and scalability. Solutions involve rigorous data preprocessing, implementing explainable AI techniques, and optimizing algorithms for efficiency and scalability.
Data Science Certification Courses in Ethiopia 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. Relevant skills, experience, and a strong foundation in mathematics and programming are crucial for success.
The operational process involves defining the problem, collecting and preprocessing data, exploratory data analysis, model development, validation, deployment, and continuous monitoring. Collaboration and communication are integral throughout the process.
In Ethiopia, a Data Scientist typically starts as an analyst, advancing to senior roles or specialized positions like machine learning engineer. Continuous learning, networking, and gaining hands-on experience contribute to career progression.
Opting for the Certified Data Scientist Course is the primary choice for aspiring data scientists in Ethiopia. This program offers extensive training in programming, statistics, and machine learning, ensuring participants acquire the necessary skills for a successful career in data science.
Statistics is fundamental in data science, aiding in data analysis, hypothesis testing, and model validation. It provides a robust framework for making informed decisions and drawing meaningful conclusions from data.
Proficiency in programming languages, data manipulation, statistical analysis, and machine learning are crucial. Strong communication, problem-solving, and critical thinking skills, along with a continuous learning mindset, contribute to success in the field.
Acquiring a strong foundation in mathematics and programming is essential. Engaging in hands-on projects, participating in online courses, and building a portfolio showcasing skills are key steps. Networking within the data science community and seeking mentorship are valuable for guidance.
Data Science bootcamps can be worthwhile for rapid skill acquisition. They offer hands-on experience, mentorship, and networking opportunities, accelerating entry into the field. However, success depends on personal commitment and the bootcamp's quality.
In finance, Data Science is applied for risk management, fraud detection, customer segmentation, and algorithmic trading. Predictive modeling and analytics enable data-driven decision-making, ultimately enhancing efficiency and innovation within the sector.
Participating in Data Science Internships in Ethiopia offers practical experience with real-world projects. It enhances hands-on skills, provides exposure to industry practices, and often leads to employment opportunities. Internships bridge the gap between academic learning and the demands of professional data science roles.
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 critical for ensuring the project aligns with business objectives and provides meaningful insights.
In Ethiopia, Data Scientists command competitive salaries, aligning with global standards. While specific figures may vary, Indeed notes that the average salary for a Data Scientist in the United States is $123,442 per year. In Ethiopia, data scientists also enjoy lucrative compensation, reflecting the high value placed on their expertise in this dynamic field.
Data Scientists collect, process, and analyze data to extract valuable insights. They develop predictive models, create data visualizations, and communicate findings to inform business strategies. Collaboration with cross-functional teams is essential for achieving organizational goals, and continuous learning is integral to staying abreast of industry advancements.
Data Science is extensively employed 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.
In e-commerce, Data Science analyzes customer behavior and transaction data to provide personalized recommendations. Recommendation systems, powered by machine learning algorithms, enhance user experiences, drive customer engagement, and contribute to increased sales and satisfaction.
Data Science focuses on extracting insights and building predictive models from complex data, often involving machine learning. Business Analytics concentrates on using data to inform business decisions, utilizing statistical analysis and descriptive analytics. While both overlap, Data Science tends to be more exploratory and predictive, while Business Analytics is often prescriptive, aiming to optimize decision-making.
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.
Engaging in DataMites' online data science training in Ethiopia brings the benefit of learning from any location, overcoming geographical limitations. The interactive online platform stimulates engagement through discussions, forums, and collaborative activities, elevating the overall data science training experience.
Absolutely, DataMites offers Data Science Courses with internships in Ethiopia, providing participants the opportunity to intern with AI companies.
The DataMites Certified Data Scientist Course in Ethiopia is globally acclaimed as the most comprehensive and job-oriented program in Data Science and Machine Learning. Regularly updated to align with industry dynamics, this course offers a structured learning experience, ensuring participants acquire essential skills for success in the data science landscape.
Navigating the Ethiopiaian data science certification domain, DataMites emerges as a prominent choice, presenting a diverse curriculum. The Certified Data Scientist course is the flagship, offering comprehensive expertise. Specialized tracks such as Data Science for Managers and Data Science Associate cater to varied proficiency levels.
The Diploma in Data Science ensures a holistic understanding. Additional courses in Statistics, Python, and domain-specific applications in Marketing, Operations, Finance, HR enrich the educational portfolio, showcasing DataMites as a versatile and reliable option for quality data science certifications in Ethiopia.
In Ethiopia, those new to data science can access beginner-level training through DataMites. The Certified Data Scientist course ensures foundational skills, while Data Science in Foundation introduces essential concepts. The Diploma in Data Science provides a comprehensive curriculum designed for beginners. These courses collectively equip individuals with the fundamental knowledge required to initiate a successful journey in the dynamic field of data science.
DataMites' data scientist courses in Ethiopia have durations ranging from 1 to 8 months, with the specific duration determined by the course level.
Certified Data Scientist Training in Ethiopia is open to beginners and intermediate learners in the field of data science, with no prerequisites.
Certainly, DataMites addresses the unique needs of working professionals with specialized data science courses like Statistics, Python, and Certified Data Scientist Operations. Tailored options in Data Science with R Programming, and Certified Data Scientist courses for Marketing, HR, and Finance ensure focused skill development.
The fee structure for DataMites' data science training in Ethiopia ranges from ETB 29,901 to ETB 74,763, offering participants various options to select a plan that suits their learning preferences and financial capacity.
DataMites chooses trainers with elite status, including faculty members with real-time experience from top companies and renowned institutes like IIMs who conduct the data science training sessions.
"Data Science for Managers" at DataMites is tailored for managers or leaders looking to seamlessly integrate data science into their decision-making processes.
Certainly, participants need to bring a valid photo identification proof, such as a national ID card or driver's license, to obtain their participation certificate and, if necessary, to schedule the certification exam during the data science training sessions.
DataMites recognizes that participants may encounter unavoidable circumstances leading to a missed data science training session in Ethiopia. To mitigate this, recorded sessions are provided for participants to catch up on the content. Additionally, personalized one-on-one sessions with trainers are available, offering guidance and addressing any questions related to the missed session.
Absolutely, DataMites includes live projects in their Data Scientist Course in Ethiopia, with a portfolio featuring more than 10 capstone projects and a meaningful client/live project.
Indeed, DataMites in Ethiopia offers a demo class option, allowing participants to explore the training content and format before committing to the fee.
Participants completing Data Science Training in Ethiopia with DataMites receive IABAC Certification, affirming their mastery in the field.
DataMites' Flexi-Pass in Ethiopia provides participants with the freedom to customize their data science training schedule, offering flexibility to fit their individual time constraints and preferences.
In Ethiopia, DataMites' career mentoring sessions adopt an inclusive format, addressing resume refinement, interview skills, and industry awareness, equipping participants for a prosperous data science career.
The available training methods for data science courses at DataMites in Ethiopia include online data science training in Ethiopia and self-paced options, allowing for flexibility and personalized learning.
Yes, upon completing the data science course with DataMites in Ethiopia, participants are granted a certification, recognizing their dedication and skills in the field.
Indeed, there is an option for help sessions with DataMites in Jordan, providing participants with dedicated support to better comprehend specific data science topics.
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.