facebook

Join Advance Training

SERVER | CLOUD | FIREWALL | DEVOPS | CYBER SECURITY | CLOUD SECURITY

Recent Plcement

Join Our 100% JOB Guarantee Program and Get Plcement in MNCs

Advance Data Analytics and Machine Learning Training

Placement Guarantee

Instructor Led Training

Get the Real Feel

Online & Offline Courses

Instructor Led Training

Stay Home and Get Trained

1-to-1 Training

Instructor Led Training

Learn with Your Own Pace

Interview Preparation

Instructor Led Training

We Come to You if You Can’t

Life Time Revision Class

Instructor Led Training

Come Back and do it again

Good Lab Setup

Instructor Led Training

Feel Live Environment

Data Analytics and Machine Learning Training Online & Offline with 100% Placement

Data Analytics and Machine Learning (ML) are in high demand. Rexton IT, a leading IT training institute, offers comprehensive online and offline training in Data Analytics and Machine Learning with a 100% Placement Guarantee. This Data Analytics course program is designed to help aspiring data professionals and career changers gain the necessary skills to excel in the industry.


Career Opportunities and Salary Insights

Data Analytics and Machine Learning professionals are among the highest-paid in the IT industry. Some of the job roles you can apply for after completing the Data Analytics course include:
  • Data Analyst (Salary: $60,000 - $100,000 Per Year)
  • Machine Learning Engineer (Salary: $80,000 - $130,000 Per Year)
  • Business Intelligence Analyst (Salary: $70,000 - $110,000 Per Year)
  • Data Scientist (Salary: $90,000 - $150,000Per Year)

Why Choose Rexton IT?

Rexton IT has established itself as a trusted name in IT training, offering industry-relevant courses with hands-on experience. Our Data Analytics and Azure course training program stands out due to the following features:
  • Industry-Driven Curriculum – Designed in collaboration with industry experts, ensuring alignment with real-world job requirements.
  • Experienced Trainers – Learn from industry professionals with extensive experience in Data Science, Analytics, and ML.
  • Hands-On Learning – Practical assignments, live projects, and case studies for an immersive learning experience.
  • Flexible Learning Modes – Both online and offline training options are available to suit different learning preferences
  • 100% Placement Assistance –Dedicated career support including resume building, interview preparation, and job referrals.
  • Certifications – Get industry-recognized certification to boost your career prospects.

Online and Offline Training Modes

Rexton IT provides both online and offline training options to accommodate different learning needs:

  • Online Training: Live instructor-led sessions, recorded lectures, virtual labs, and 24/7 learning support.
  • Offline Training: Classroom-based training with face-to-face interaction, lab access, and hands-on project work.

Start Free Trial Today

  • United States+1
  • United Kingdom+44
  • Afghanistan (‫افغانستان‬‎)+93
  • Albania (Shqipëri)+355
  • Algeria (‫الجزائر‬‎)+213
  • American Samoa+1
  • Andorra+376
  • Angola+244
  • Anguilla+1
  • Antigua and Barbuda+1
  • Argentina+54
  • Armenia (Հայաստան)+374
  • Aruba+297
  • Ascension Island+247
  • Australia+61
  • Austria (Österreich)+43
  • Azerbaijan (Azərbaycan)+994
  • Bahamas+1
  • Bahrain (‫البحرين‬‎)+973
  • Bangladesh (বাংলাদেশ)+880
  • Barbados+1
  • Belarus (Беларусь)+375
  • Belgium (België)+32
  • Belize+501
  • Benin (Bénin)+229
  • Bermuda+1
  • Bhutan (འབྲུག)+975
  • Bolivia+591
  • Bosnia and Herzegovina (Босна и Херцеговина)+387
  • Botswana+267
  • Brazil (Brasil)+55
  • British Indian Ocean Territory+246
  • British Virgin Islands+1
  • Brunei+673
  • Bulgaria (България)+359
  • Burkina Faso+226
  • Burundi (Uburundi)+257
  • Cambodia (កម្ពុជា)+855
  • Cameroon (Cameroun)+237
  • Canada+1
  • Cape Verde (Kabu Verdi)+238
  • Caribbean Netherlands+599
  • Cayman Islands+1
  • Central African Republic (République centrafricaine)+236
  • Chad (Tchad)+235
  • Chile+56
  • China (中国)+86
  • Christmas Island+61
  • Cocos (Keeling) Islands+61
  • Colombia+57
  • Comoros (‫جزر القمر‬‎)+269
  • Congo (DRC) (Jamhuri ya Kidemokrasia ya Kongo)+243
  • Congo (Republic) (Congo-Brazzaville)+242
  • Cook Islands+682
  • Costa Rica+506
  • Côte d’Ivoire+225
  • Croatia (Hrvatska)+385
  • Cuba+53
  • Curaçao+599
  • Cyprus (Κύπρος)+357
  • Czech Republic (Česká republika)+420
  • Denmark (Danmark)+45
  • Djibouti+253
  • Dominica+1
  • Dominican Republic (República Dominicana)+1
  • Ecuador+593
  • Egypt (‫مصر‬‎)+20
  • El Salvador+503
  • Equatorial Guinea (Guinea Ecuatorial)+240
  • Eritrea+291
  • Estonia (Eesti)+372
  • Eswatini+268
  • Ethiopia+251
  • Falkland Islands (Islas Malvinas)+500
  • Faroe Islands (Føroyar)+298
  • Fiji+679
  • Finland (Suomi)+358
  • France+33
  • French Guiana (Guyane française)+594
  • French Polynesia (Polynésie française)+689
  • Gabon+241
  • Gambia+220
  • Georgia (საქართველო)+995
  • Germany (Deutschland)+49
  • Ghana (Gaana)+233
  • Gibraltar+350
  • Greece (Ελλάδα)+30
  • Greenland (Kalaallit Nunaat)+299
  • Grenada+1
  • Guadeloupe+590
  • Guam+1
  • Guatemala+502
  • Guernsey+44
  • Guinea (Guinée)+224
  • Guinea-Bissau (Guiné Bissau)+245
  • Guyana+592
  • Haiti+509
  • Honduras+504
  • Hong Kong (香港)+852
  • Hungary (Magyarország)+36
  • Iceland (Ísland)+354
  • India (भारत)+91
  • Indonesia+62
  • Iran (‫ایران‬‎)+98
  • Iraq (‫العراق‬‎)+964
  • Ireland+353
  • Isle of Man+44
  • Israel (‫ישראל‬‎)+972
  • Italy (Italia)+39
  • Jamaica+1
  • Japan (日本)+81
  • Jersey+44
  • Jordan (‫الأردن‬‎)+962
  • Kazakhstan (Казахстан)+7
  • Kenya+254
  • Kiribati+686
  • Kosovo+383
  • Kuwait (‫الكويت‬‎)+965
  • Kyrgyzstan (Кыргызстан)+996
  • Laos (ລາວ)+856
  • Latvia (Latvija)+371
  • Lebanon (‫لبنان‬‎)+961
  • Lesotho+266
  • Liberia+231
  • Libya (‫ليبيا‬‎)+218
  • Liechtenstein+423
  • Lithuania (Lietuva)+370
  • Luxembourg+352
  • Macau (澳門)+853
  • Macedonia (FYROM) (Македонија)+389
  • Madagascar (Madagasikara)+261
  • Malawi+265
  • Malaysia+60
  • Maldives+960
  • Mali+223
  • Malta+356
  • Marshall Islands+692
  • Martinique+596
  • Mauritania (‫موريتانيا‬‎)+222
  • Mauritius (Moris)+230
  • Mayotte+262
  • Mexico (México)+52
  • Micronesia+691
  • Moldova (Republica Moldova)+373
  • Monaco+377
  • Mongolia (Монгол)+976
  • Montenegro (Crna Gora)+382
  • Montserrat+1
  • Morocco (‫المغرب‬‎)+212
  • Mozambique (Moçambique)+258
  • Myanmar (Burma) (မြန်မာ)+95
  • Namibia (Namibië)+264
  • Nauru+674
  • Nepal (नेपाल)+977
  • Netherlands (Nederland)+31
  • New Caledonia (Nouvelle-Calédonie)+687
  • New Zealand+64
  • Nicaragua+505
  • Niger (Nijar)+227
  • Nigeria+234
  • Niue+683
  • Norfolk Island+672
  • North Korea (조선 민주주의 인민 공화국)+850
  • Northern Mariana Islands+1
  • Norway (Norge)+47
  • Oman (‫عُمان‬‎)+968
  • Pakistan (‫پاکستان‬‎)+92
  • Palau+680
  • Palestine (‫فلسطين‬‎)+970
  • Panama (Panamá)+507
  • Papua New Guinea+675
  • Paraguay+595
  • Peru (Perú)+51
  • Philippines+63
  • Poland (Polska)+48
  • Portugal+351
  • Puerto Rico+1
  • Qatar (‫قطر‬‎)+974
  • Réunion (La Réunion)+262
  • Romania (România)+40
  • Russia (Россия)+7
  • Rwanda+250
  • Saint Barthélemy+590
  • Saint Helena+290
  • Saint Kitts and Nevis+1
  • Saint Lucia+1
  • Saint Martin (Saint-Martin (partie française))+590
  • Saint Pierre and Miquelon (Saint-Pierre-et-Miquelon)+508
  • Saint Vincent and the Grenadines+1
  • Samoa+685
  • San Marino+378
  • São Tomé and Príncipe (São Tomé e Príncipe)+239
  • Saudi Arabia (‫المملكة العربية السعودية‬‎)+966
  • Senegal (Sénégal)+221
  • Serbia (Србија)+381
  • Seychelles+248
  • Sierra Leone+232
  • Singapore+65
  • Sint Maarten+1
  • Slovakia (Slovensko)+421
  • Slovenia (Slovenija)+386
  • Solomon Islands+677
  • Somalia (Soomaaliya)+252
  • South Africa+27
  • South Korea (대한민국)+82
  • South Sudan (‫جنوب السودان‬‎)+211
  • Spain (España)+34
  • Sri Lanka (ශ්‍රී ලංකාව)+94
  • Sudan (‫السودان‬‎)+249
  • Suriname+597
  • Svalbard and Jan Mayen+47
  • Sweden (Sverige)+46
  • Switzerland (Schweiz)+41
  • Syria (‫سوريا‬‎)+963
  • Taiwan (台灣)+886
  • Tajikistan+992
  • Tanzania+255
  • Thailand (ไทย)+66
  • Timor-Leste+670
  • Togo+228
  • Tokelau+690
  • Tonga+676
  • Trinidad and Tobago+1
  • Tunisia (‫تونس‬‎)+216
  • Turkey (Türkiye)+90
  • Turkmenistan+993
  • Turks and Caicos Islands+1
  • Tuvalu+688
  • U.S. Virgin Islands+1
  • Uganda+256
  • Ukraine (Україна)+380
  • United Arab Emirates (‫الإمارات العربية المتحدة‬‎)+971
  • United Kingdom+44
  • United States+1
  • Uruguay+598
  • Uzbekistan (Oʻzbekiston)+998
  • Vanuatu+678
  • Vatican City (Città del Vaticano)+39
  • Venezuela+58
  • Vietnam (Việt Nam)+84
  • Wallis and Futuna (Wallis-et-Futuna)+681
  • Western Sahara (‫الصحراء الغربية‬‎)+212
  • Yemen (‫اليمن‬‎)+967
  • Zambia+260
  • Zimbabwe+263
  • Åland Islands+358

Go To Next Level in IT

Get Certified and Stay Updated

Key Benefits of Rexton IT's Data Analytics and Machine Learning Training

Rexton IT offers comprehensive training in Data Analytics and Machine Learning, covering Python, SQL, Excel, Power BI, and Tableau, both online and offline, with a 100% placement guarantee. This training is designed for fresh graduates, working professionals, and career changers looking to establish themselves in the lucrative field of data analytics and machine learning.

 

Master Industry-Standard Tools and Technologies

Rexton IT’s training covers the most in-demand tools used by data analysts and machine learning engineers:
  • Python: One of the most popular programming languages for data analysis and machine learning due to its powerful libraries like Pandas, NumPy, Scikit-learn, and TensorFlow.
  • SQL: Essential for data extraction, transformation, and querying databases.
  • Excel: Widely used for data manipulation, visualization, and basic analytics.
  • Power BI: A powerful business intelligence tool used for interactive visualizations and reporting.
  • Tableau: One of the leading data visualization tools used in businesses worldwide.
 

Comprehensive and Practical Curriculum

Industry experts design Rexton IT’s Data Analytics course to ensure learners gain practical, job-relevant skills. The curriculum includes:
  • Fundamentals of Data Analytics: Understanding data structures, processing, and visualization.
  • Data Cleaning and Preprocessing: Techniques for handling missing data and preparing datasets.
  • Exploratory Data Analysis (EDA): Identifying patterns and insights from data.
  • Machine Learning Algorithms: Supervised and unsupervised learning, model building, and evaluation.
  • Data Visualization: Creating dashboards and reports using Power BI and Tableau.
  • Big Data and Cloud Computing: Introduction to handling large datasets using cloud-based platforms.

 

100% Placement Guaranteed 

One of the standout features of Rexton IT’s Data Analytics course training is its 100% placement guarantee. It includes:
  • Resume Building: Expert guidance on crafting a professional resume highlighting data analytics and machine learning skills.
  • Interview Preparation: Mock interviews, technical assessments, and soft skills training.
  • Job Referrals: Partnerships with top IT and consulting firms to connect learners with potential employers.
  • Career Mentorship: Ongoing career support to help candidates secure high-paying jobs.
 

Start Your Journey Today

Select Your Career Path
  • What is your experience with data analysis and what tools do you use?
  • How do you approach a data analysis project from start to finish?
  • What is your understanding of statistical analysis and how do you apply it to your work?
  • How do you handle missing data or outliers in your analysis?
  • How do you ensure the quality and accuracy of your data analysis?
  • How do you communicate your findings and insights to stakeholders who may not have a background in data analysis?
  • What is your experience with SQL and databases?
  • What is your experience with programming languages such as Python or R?
  • Can you explain a data analysis project you worked on that utilized machine learning techniques?
  • How do you evaluate the effectiveness of a machine learning model?
  • How do you handle imbalanced data sets in machine learning?
  • Can you explain the difference between supervised and unsupervised learning?
  • What is your experience with data visualization tools such as Tableau or Power BI?
  • Can you explain a data visualization project you worked on and how you chose the appropriate visualization techniques?
  • What is your experience with big data technologies such as Hadoop or Spark?
  • How do you handle scalability in data analysis projects?
  • Can you explain a project you worked on where you utilized data mining techniques?
  • What is your experience with data warehousing and ETL processes?
  • How do you handle data security and privacy concerns in your analysis?
  • What is your experience with cloud-based data analysis tools.
  • What is machine learning and how does it differ from traditional programming?
  • What are the different types of machine learning algorithms?
  • What is the difference between supervised and unsupervised learning?
  • What is the difference between classification and regression?
  • What is overfitting and how can it be avoided?
  • What is the bias-variance tradeoff?
  • What is cross-validation and why is it important?
  • What is regularization and why is it used?
  • What is the curse of dimensionality and how can it be addressed?
  • What is ensemble learning and how does it work?
  • What is deep learning and how is it used?
  • What is backpropagation and how is it used in neural networks?
  • What is a convolutional neural network and how is it different from other neural networks?
  • What is a recurrent neural network and how is it used?
  • What is transfer learning and how is it used in machine learning?
  • What is reinforcement learning and how is it used?
  • What is the difference between batch learning and online learning?
  • What is the difference between a generative model and a discriminative model?
  • What is the difference between a parametric model and a non-parametric model?
  • What is the difference between a decision tree and a random forest?
  • What is the difference between K-means and hierarchical clustering?
  • What is support vector machine and how does it work?
  • What is the difference between linear regression and logistic regression?
  • What is the ROC curve and why is it used?
  • What is precision and recall and how are they used in classification models?

Why Choose us

Innovative Solutions For You

Our team offers unparalleled knowledge in Cisco networking and Palo Alto security, backed by industry-leading certifications and hands-on experience. We are committed to delivering customized, efficient, and secure network solutions tailored to your specific needs. Our proven track record, customer-centric approach, and continuous support ensure that your network infrastructure is robust, reliable, and future-ready. By choosing us, you’re partnering with professionals dedicated to driving your success through innovative technology and exceptional service.

Certified Professional & Experts

Our certified professionals and experts deliver top-notch solutions, ensuring excellence and reliability in every project we undertake.

Industry-oriented curriculum

Our industry-oriented curriculum ensures students gain practical skills and knowledge, preparing them for real-world challenges and career success.

AI-driven learning products

AI-driven learning products deliver personalized education, enhancing engagement, efficiency, and outcomes by adapting to individual learning styles.

Ans- Data Analytics is the process of analyzing raw data to find trends, patterns, and insights to make informed business decisions.

Ans- Data Analytics and Azure course are in high demand across industries, offering lucrative career opportunities in business intelligence, finance, healthcare, marketing, and more.

Ans- Most courses require basic knowledge of mathematics, statistics, and familiarity with Excel. Some advanced courses may require programming knowledge (Python, SQL, or R).

Ans- Anyone interested in data, including students, fresh graduates, working professionals, and career changers.

Ans- Topics typically include data cleaning, data visualization, statistical analysis, SQL, Python/R /R, machine learning basics, and business intelligence tools.

Ans- Entry-level analysts earn around $50,000-$70,000, while experienced analysts make over $100,000 annually.

OUR PLACEMENT

blog thumb
blog thumb
blog thumb
blog thumb
blog thumb
blog thumb

Choose Other Training Courses

course
Advance Data Analytics and Machine Learning Training
Rating
fst fst