Instructor Led Live Online
Self Learning + Live Mentoring
In - Person Classroom 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 is a multidisciplinary field that involves extracting insights and knowledge from structured and unstructured data using various techniques such as data analysis, statistics, machine learning, and data visualization.
Learning data science is important because it enables individuals and organizations to make data-driven decisions, uncover hidden patterns and trends, and gain valuable insights that can lead to improved business strategies, efficiency, and innovation.
Essential skills for becoming a data scientist include proficiency in programming languages like Python or R, knowledge of statistics and mathematics, data manipulation and analysis skills, machine learning expertise, data visualization, and effective communication and storytelling abilities.
Effective learning of data science involves a combination of theoretical understanding, hands-on practice with real-world datasets, participating in projects and competitions, continuous learning and updating of skills, and leveraging online resources, courses, and mentorship.
Data scientists often face challenges such as dealing with large and complex datasets, data cleaning and preprocessing, selecting appropriate algorithms and models, handling missing or noisy data, interpreting results accurately, and staying updated with the rapidly evolving field.
The cost of a data science course in Lucknow can vary depending on the institution and program, but it generally ranges from INR 40,000 to INR 50,000.
The requirements to enrol in a data science course can vary but typically include a basic understanding of programming, mathematics, and statistics. Some courses may have prerequisites or recommended knowledge in specific areas.
Data science offers promising career prospects with a high demand for skilled professionals in various industries such as technology, finance, healthcare, marketing, and more. Job roles in data science include data scientist, data analyst, machine learning engineer, data engineer, and business analyst, among others.
Obtaining a certification in data science is important as it demonstrates proficiency and credibility in the field, enhances job prospects, and provides validation of skills and knowledge to potential employers.
Yes, data science courses are in high demand as organizations increasingly recognize the value of data-driven decision-making and require skilled professionals to extract insights from data and drive business success.
Data science is considered a secure career choice due to the growing demand for data professionals across industries. However, it is important to continuously update skills and stay abreast of industry trends to maintain a competitive edge.
The difficulty level in studying data science can vary depending on individual aptitude, prior knowledge, and the depth of the subject matter. It requires a strong foundation in mathematics, statistics, and programming, but with dedication and practice, it can be mastered.
Python is widely used and highly recommended for data science due to its rich ecosystem of libraries and tools for data analysis, machine learning, and visualization. However, proficiency in other languages like R or SQL can also be beneficial depending on specific requirements.
SQL (Structured Query Language) is important for data science as it allows for efficient querying and manipulation of relational databases. It is useful for data extraction, cleaning, and aggregation tasks, which are common in data science projects.
A strong background in statistics is crucial for data science as it provides the foundation for understanding and interpreting data, selecting appropriate statistical techniques and models, and evaluating the significance and reliability of results.
DataMites in Lucknow stands out as an excellent choice for those interested in pursuing a Data Science course. It sets itself apart with its highly skilled instructors, an extensive curriculum that encompasses various data science subjects, an emphasis on practical learning through hands-on exercises, industry-oriented projects, and dedicated support in finding placement opportunities.
The DataMites Certified Data Scientist Course in Lucknow extends a warm welcome to individuals with a strong foundation in mathematics and programming, as well as those with prior experience in statistics, engineering, or related fields. This inclusive approach enables a diverse range of participants to pursue their career aspirations in the dynamic field of Data Science.
Opting for the DataMites data science course in Lucknow is a wise choice, given its thoughtfully designed curriculum, knowledgeable faculty, engaging hands-on learning opportunities, practical project assignments, and industry-focused training. This all-encompassing program significantly improves your comprehension and expertise in the field of data science, thereby bolstering your chances of securing employment.
The course extends for a duration of 8 months, comprising 700 learning hours, out of which 120 hours are dedicated to live online training.
Upon the successful completion of the data science course in Lucknow, students receive the prestigious IABAC certification, which holds substantial global recognition. This esteemed certification serves as a valuable credential, enhancing job prospects and enabling participation in internship programs, thus unlocking numerous opportunities within the field of data science.
After completing the course, DataMites provides strong support and guidance for placements through their dedicated Placement Assistance Team (PAT). The PAT offers personalized assistance to individuals, ensuring they receive comprehensive support in finding suitable job placements. This tailored support greatly improves employment prospects and opens up a wide range of opportunities in the field of data science.
DataMites provides a wide selection of data science courses in Lucknow, encompassing a diverse range of topics. These courses include Data Science Foundation, Data Science for Managers, Data Science Associate, Diploma in Data Science, Python for Data Science, Statistics for Data Science, Data Science Marketing, Data Science Operations, Data Science Retail, Data Science for HR, Data Science with Finance, and Data Science.
DataMites is widely recognized for its outstanding team of industry-expert educators who have deep expertise and extensive experience in the field of data science. These instructors are highly qualified, hold prestigious certifications, and bring their wealth of knowledge to the classroom, delivering exceptional instruction. With their guidance, students are empowered to develop a comprehensive understanding of the subject matter
DataMites recognizes the diverse preferences of students and offers flexible learning options to accommodate their needs. They provide a range of choices, including live online sessions, self-paced learning, and on-demand classroom training. This flexibility allows individuals to select the learning approach that best suits their requirements, making it convenient for them to pursue their data science education.
DataMites provides a comprehensive overview of its training approach, ensuring students have a clear understanding of the training process and its elements. Additionally, they offer a complimentary demo class, allowing individuals to fully grasp the training methodology. This enables prospective students to evaluate the quality and suitability of the training before making a commitment, ensuring an informed decision.
Learning Through Case Study Approach
Theory → Hands-on → Case Study → Project → Model Deployment
The payment mode available for the data science course in Lucknow through:
DataMites provides its Data Science Course in Lucknow at various price points, offering a variety of options to accommodate different preferences. These include INR 35,000 for live online training, INR 21,000 for blended learning, and INR 44,000 for on-demand classroom training. This flexible pricing structure allows individuals to choose the plan that suits their budget and preferred mode of learning.
To obtain the participation certificate and book the certification exam, it is essential to submit valid photo identification proofs, such as a National ID card or a Driving license. These identification proofs play a crucial role in ensuring the authenticity and accuracy of the certification process.
According to a PayScale report, the salary of a data scientist in India ranges from INR 9,10,238 per year.
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.